eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada

Article

Jamei, Mehdi, Farooque, Aitazaz Ahsan, Ali, Mumtaz, Karbasi, Masoud, Afzaal, Hassan, Cheema, Saad Javed, Zaman, Qamar Uz, Woon, Kok Sin and Sheridan, Paul. 2025. "eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada." Computers and Electronics in Agriculture. 238. https://doi.org/10.1016/j.compag.2025.110831
Article Title

eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada

ERA Journal ID41630
Article CategoryArticle
AuthorsJamei, Mehdi, Farooque, Aitazaz Ahsan, Ali, Mumtaz, Karbasi, Masoud, Afzaal, Hassan, Cheema, Saad Javed, Zaman, Qamar Uz, Woon, Kok Sin and Sheridan, Paul
Journal TitleComputers and Electronics in Agriculture
Journal Citation238
Article Number110831
Number of Pages24
Year2025
PublisherElsevier
Place of PublicationNetherlands
ISSN0168-1699
Digital Object Identifier (DOI)https://doi.org/10.1016/j.compag.2025.110831
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0168169925009378
Abstract

The potato crop is vital to the economy of Canada’s Maritime provinces. Prince Edward Island (PEI) and New Brunswick (NB) contribute significantly to Canadian potato production and gross domestic product (GDP). Estimating potato tuber yields helps farmers to make informed decisions for sustainable and profitable farming. This study investigated fluctuations in tuber yield based on 30 soil properties gathered over four seasons through experimental trials. An emerging eXplainable high-dimensional feature vote-based ensemble framework explained with SHAP (SHapley Additive exPlanations) tool was employed to estimate potato tuber yield accurately. In order to develop the model, the most influential feature was first filtered using the Boruta-SHAP feature selection. Afterwards, the most deserved combinations (four scenarios) were ascertained using the best subset regression (BSR) integrated with two Multi-Criteria Decision-Making (MCDM), namely Weighted Aggregated Sum Product Assessment (WASPAS) and Multi-Objective Optimization methods were adopted based on the Ratio Analysis (MOORA). To estimate potato tuber yield, we adopted a novel explainable ensemble machine learning model, called VOTE-LGCB, that combines voted Categorical Boosting and the Light Gradient-Boosting Machine framework. We evaluated our approach against Least Absolute Shrinkage and Selection Operator (LASSO) regression, elastic net regression, Extra Tree, classical LightGBM, and classical CatBoost baselines. Six metric performances such as correlation coefficient (R), root mean square error (RMSE), and reliability were implemented to validate the multi-process ML models. All the metrics were singularized using WASPAS and MOORA to determine the best input combination related to each model separately. We found that the VOTE-LGCB-Combo 3 outperformed baseline methods (R = 0.8958, RMSE = 5088.5087, Reliability = 93.7500, WASPAS = 0.00023, and MOORA = 0.3788). Moisture content was identified as the most significant feature, followed by the Normalized Difference Vegetation Index (NDVI). The modeling framework we advance can be used as a reliable simulation system for various aspects of agricultural production systems that involve high-dimensional features.

KeywordsPotato tuber yield; Explainable machine learning; MOORA; LightGBM; Boruta-SHAP; CatBoost
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020461103. Deep learning
460207. Modelling and simulation
Byline AffiliationsUniversity of Prince Edward Island, Canada
Shahid Chamran University of Ahvaz, Iran
UniSQ College
Dalhousie University, Canada
Hong Kong University of Science and Technology, China
Permalink -

https://research.usq.edu.au/item/zz19x/explainable-expert-systems-for-potato-tuber-yield-prediction-in-the-maritime-provinces-of-canada

Log in to edit

Download files

Published Version
eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada.pdf
License: CC BY-NC-ND 4.0
File access level: Anyone

  • 14
    total views
  • 1
    total downloads
  • 0
    views this month
  • 1
    downloads this month

Export as

Related outputs

Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model
Alabdally, Hussein, Ali, Mumtaz, Diykh, Mohammad, Deo, Ravinesh C., Aldhafeeri, Anwar Ali, Abdulla, Shahab and Farooque, Aitazaz Ahsan. 2025. "Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model." Forecasting. 7 (3). https://doi.org/10.3390/forecast7030046
Multi-step ahead significant wave height forecasting using global and local view graph representation based on GRU model
Diykh, Mohammed, Ali, Mumtaz, Jamei, Mehdi, Prasad, Ramendra, Labban, Abdulhaleem H., Abdulla, Shahab, Singh, Niharika and Farooque, Aitazaz Ahsan. 2025. "Multi-step ahead significant wave height forecasting using global and local view graph representation based on GRU model." Ocean Engineering. 340 (Part 2). https://doi.org/10.1016/j.oceaneng.2025.122314
Uncertainty assessment based on data decomposition and Boruta-driven extreme gradient boosting to predict spatiotemporal urban air dust heavy metal index
Seifi, Akram, Soltani-Gerdefaramarzi, Somayeh and Ali, Mumtaz. 2025. "Uncertainty assessment based on data decomposition and Boruta-driven extreme gradient boosting to predict spatiotemporal urban air dust heavy metal index." Atmospheric Pollution Research. 16 (11). https://doi.org/10.1016/j.apr.2025.102654
Designing advanced feature selection and uncertainty quantification-based deep learning approach to predict chlorophyll-a and water bloom risks in dam reservoir
Seifi, Akram, Madvar, Hossien Riahi, Davarpanah, Rouhollah, Ali, Mumtaz and Mashat, Abdul-Wahab. 2025. "Designing advanced feature selection and uncertainty quantification-based deep learning approach to predict chlorophyll-a and water bloom risks in dam reservoir." Journal of Water Process Engineering. 77. https://doi.org/10.1016/j.jwpe.2025.108341
Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia
Aldhafiri, Anwar Ali, Ali, Mumtaz and Labban, Abdulhaleem H.. 2025. "Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia." Water. 17 (11). https://doi.org/10.3390/w17111699
Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands
Chand, Ravinesh, Deo, Ravinesh C., Ghimire, Sujan, Nguyen-Huy, Thong and Ali, Mumtaz. 2025. "Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands." Stochastic Environmental Research and Risk Assessment. 39 (5), pp. 2203-2229. https://doi.org/10.1007/s00477-025-02964-8
Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms
Khosravi, Khabat, Mosallanejad, Ashkan, Bateni, Sayed M., Kim, Dongkyun, Jun, Changhyun, Shahvaran, Ali Reza, Farooque, Aitazaz A., Karbasi, Massoud and Ali, Mumtaz. 2025. "Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms." Science of the Total Environment. 977. https://doi.org/https://doi.org/10.1016/j.scitotenv.2025.179369
Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms
Khosravi, Khabat, Farooque, Aitazaz Ahsan, Karbasi, Masoud, Ali, Mumtaz, Heddam, Salim, Faghfouri, Ali and Abolfathi, Soroush. 2025. "Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms." Environmental Science and Pollution Research. 32 (11), pp. 6405-6424. https://doi.org/10.1007/s11356-025-36062-7
A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting
Ahmadianfar, Iman, Farooque, Aitazaz Ahsan, Ali, Mumtaz, Jamei, Mehdi, Jamei, Mozhdeh and Yaseen, Zaher Mundher. 2025. "A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting." Scientific Reports. 15. https://doi.org/10.1038/s41598-025-90628-6
Systematic Review of AI and Machine Learning Approaches for Predicting Crop Diseases in the Context of Climate Change and the Food Security
Kaur, Avneet, Randhawa, Gurjit S., Farooque, Aitazaz A., Singh, Rajandeep, Ali, Mumtaz and Zaman, Qamar U.. 2025. "Systematic Review of AI and Machine Learning Approaches for Predicting Crop Diseases in the Context of Climate Change and the Food Security." Filho, Walter Leal, Matandirotya, Newton, Ayal, Desalegn Yayeh, Luetz, Johannes M. and Borsari, Bruno (ed.) Climate Change, Food Security, and Land Management: Strategies for a Sustainable Future. Switzerland. Springer. pp. 1-20
Designing empirical fourier decomposition reinforced with multiscale increment entropy and deep learning to forecast dry bulb air temperature
Diykh, Mohammed, Ali, Mumtaz, Labban, Abdulhaleem H., Prasad, Ramendra, Jamei, Mehdi, Abdulla, Shahab and Farooque, Aitazaz Ahsan. 2025. "Designing empirical fourier decomposition reinforced with multiscale increment entropy and deep learning to forecast dry bulb air temperature." Results in Engineering. 26. https://doi.org/10.1016/j.rineng.2025.104597
Multi‑step solar ultraviolet index prediction: integrating convolutional neural networks with long short‑term memory for a representative case study in Queensland, Australia
AL-Musaylh, Mohan, Al‑Dafaie, Kadhem, Downs, Nathan, Ghimire, Sujan, Ali, Mumtaz, Yaseen, Zaher Mundher, Igoe, Damien P., Deo, Ravinesh C., Paris, Alfo V. and A. Jebar, Mustapha A.. 2025. "Multi‑step solar ultraviolet index prediction: integrating convolutional neural networks with long short‑term memory for a representative case study in Queensland, Australia." Modeling Earth Systems and Environment. 11. https://doi.org/10.1007/s40808-024-02282-y
Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory
Ali, Mumtaz, Nayahi, Jesu Vedha, Abdi, Erfan, Ghorbani, Mohammad Ali, Mohajeri, Farzan, Farooque, Aitazaz A. and Alamery, Salman. 2025. "Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory ." Ecological Informatics. 85. https://doi.org/10.1016/j.ecoinf.2025.102995
A Review of APHRODITE Performance in Asia: Current Status and Research Concerns
Tan, Mou Leong, Goliatt, Leonardo, Heddam, Salim, Maulud, Khairul Nizam Abdul, Halder, Bijay, Sa’adi, Zulfaqar, Ahmadianfar, Iman, Shafik, Shafik S., Ali, Mumtaz and Yaseen, Zaher Mundher. 2025. "A Review of APHRODITE Performance in Asia: Current Status and Research Concerns." Journal of Hydrology. 651. https://doi.org/10.1016/j.jhydrol.2024.132562
An Explainable Predictive Approach for Investigation of Greenhouse Gas Emissions in Maritime Canada's Potato Agriculture
Jamei, Mehdi, Yaqoob, Nauman, Farooque, Aitazaz A., Ali, Mumtaz, Malik, Anurag, Esau, Travis J. and Hu, Yulin. 2025. "An Explainable Predictive Approach for Investigation of Greenhouse Gas Emissions in Maritime Canada's Potato Agriculture." Smart Agricultural Technology . 10. https://doi.org/10.1016/j.atech.2024.100709
Near real-time significant wave height prediction along the coastline of Queensland using advanced hybrid machine learning models
Khosravi, K., Ali, M. and Heddam, S.. 2025. "Near real-time significant wave height prediction along the coastline of Queensland using advanced hybrid machine learning models." International Journal of Environmental Science and Technology. 22 (7), pp. 5309-5326. https://doi.org/10.1007/s13762-024-05944-7
Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review
Kaur, Avneet, Randhawa, Gurjit S., Abbas, Farhat, Ali, Mumtaz, Esau, Travis J., Farooque, Aitazaz A. and Singh, Rajandeep. 2024. "Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review." IEEE Access. 12, pp. 193902-193922. https://doi.org/10.1109/ACCESS.2024.3510456
Forecasting River Water Temperature Using Explainable Artificial Intelligence and Hybrid Machine Learning: Case Studies in Menindee Region in Australia
Briceno Medina, Leyde, Joehnk, Klaus, Deo, Ravinesh C., Ali, Mumtaz, Prasad, Salvin S. and Downs, Nathan. 2024. "Forecasting River Water Temperature Using Explainable Artificial Intelligence and Hybrid Machine Learning: Case Studies in Menindee Region in Australia." Water. 16 (24). https://doi.org/10.3390/w16243720
A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation
Ali, Mumtaz, Prasad, Ramendra, Alamery, Salman and Farooque, Aitazaz Ahsan. 2024. "A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation." Results in Engineering. 24. https://doi.org/10.1016/j.rineng.2024.103607
Monitoring of Greenhouse Gas Emission Drivers in Atlantic Canadian Potato Production: A Robust Explainable Intelligent Glass-Box
Jamei, Mehdi, Hassan, Muhammad, Farooque, Aitazaz A., Ali, Mumtaz, Karbasi, Masoud, Randhawa, Gurjit, Yaseen, Zaher Mundher and Dwyer, Ross. 2024. "Monitoring of Greenhouse Gas Emission Drivers in Atlantic Canadian Potato Production: A Robust Explainable Intelligent Glass-Box." Results in Engineering. 24. https://doi.org/10.1016/j.rineng.2024.103297
Innovative Multi-Temporal Evapotranspiration Forecasting Using Empirical Fourier Decomposition and Bidirectional Long Short-Term Memory
Karbasi, Masoud, Ali, Mumtaz, Randhawa, Gurjit S., Jamei, Mehdi, Malik, Anurag, Hussain, Syed Hamid Hussain, Bos, Melanie, Zaman, Qamar and Farooque, Aitazaz Ahsan. 2024. "Innovative Multi-Temporal Evapotranspiration Forecasting Using Empirical Fourier Decomposition and Bidirectional Long Short-Term Memory." Smart Agricultural Technology . 9. https://doi.org/10.1016/j.atech.2024.100619
Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm
Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2024. "Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm." Scientific Reports. 14 (1). https://doi.org/10.1038/s41598-024-69309-3
Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting
Karbasi, Masoud, Ali, Mumtaz, Farooque, Aitazaz Ahsan, Jamei, Mehdi, Khosravi, Khabat, Cheema, Saad Javed and Yaseen, Zaher Mundher. 2024. "Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting." Expert Systems with Applications. 256. https://doi.org/10.1016/j.eswa.2024.124900
Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm
Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2024. "Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm." Scientific Reports. 14. https://doi.org/10.1038/s41598-024-65837-0
Enhancing groundwater level prediction accuracy using interpolation techniques in deep learning models
Abdi, Erfan, Ali, Mumtaz, Guimarães Santos, Celso Augusto, Olusola, Adeyemi and Ghorbani, Mohammad Ali. 2024. "Enhancing groundwater level prediction accuracy using interpolation techniques in deep learning models." Groundwater for Sustainable Development. 26. https://doi.org/10.1016/j.gsd.2024.101213
Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index
Chand, Ravinesh, Nguyen-Huy, Thong, Deo, Ravinesh C., Ghimire, Sujan, Ali, Mumtaz and Ghahramani, Afshin. 2024. "Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index." Water. 16 (11). https://doi.org/10.3390/w16111560
Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data
Diykh, Mohammed, Ali, Mumtaz, Jamei, Mehdi, Abdulla, Shahab, Uddin, Md Palash, Farooque, Aitazaz Ahsan, Labban, Abdulhaleem H. and Alabdally, Hussein. 2024. "Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data." Computers and Electronics in Agriculture. 221. https://doi.org/10.1016/j.compag.2024.108964
Quantitative improvement of streamflow forecasting accuracy in the Atlantic zones of Canada based on hydro-meteorological signals: A multi-level advanced intelligent expert framework
Jamei, Mozhdeh, Jamei, Mehdi, Ali, Mozhdeh, Karbasi, Masoud, Farooque, Aitazaz A., Malik, Anurag, Cheema, Saad Javed, Esau, Travis J. and Yaseen, Zaher Mundher. 2024. "Quantitative improvement of streamflow forecasting accuracy in the Atlantic zones of Canada based on hydro-meteorological signals: A multi-level advanced intelligent expert framework." Ecological Informatics. 80. https://doi.org/10.1016/j.ecoinf.2023.102455
Short-term drought Index forecasting for hot and semi-humid climate Regions: A novel empirical Fourier decomposition-based ensemble Deep-Random vector functional link strategy
Jamei, Mehdi, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Karbasi, Masoud, Malik, Anurag, Jamei, Mozhdeh and Yaseen, Zaher Mundher. 2024. "Short-term drought Index forecasting for hot and semi-humid climate Regions: A novel empirical Fourier decomposition-based ensemble Deep-Random vector functional link strategy ." Computers and Electronics in Agriculture. 217. https://doi.org/10.1016/j.compag.2023.108609
Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks
Ali, Mumtaz, Prasad, Ramendra, Jamei, Mehdi, Malik, Anurag, Xiang, Yong, Abdulla, Shahab, Deo, Ravinesh C., Farooque, Aitazaz A. and Labban, Abdulhaleem H.. 2024. "Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks." Renewable Energy. 221. https://doi.org/10.1016/j.renene.2023.119773
Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest
Jamei, Mehdi, Ali, Mumtaz, Afzaal, Hassan, Karbasi, Masoud, Malik, Anurag, Farooque, Aitazaz Ahsan, Haydar, Zeeshan and Zaman, Qamar Uz. 2024. "Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest." Computers and Electronics in Agriculture. 216. https://doi.org/10.1016/j.compag.2023.108479
Application of an explainable glass-box machine learning approach for prognostic analysis of a biogas-powered small agriculture engine
Jamei, Mehdi, Sharma, Prabhakar, Ali, Mumtaz, Bora, Bhaskor J., Malik, Anurag, Paramasivam, Prabhu, Farooque, Aitazaz A. and Abdulla, Shahab. 2024. "Application of an explainable glass-box machine learning approach for prognostic analysis of a biogas-powered small agriculture engine." Energy. 288. https://doi.org/https://doi.org/10.1016/j.energy.2023.129862
Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition
Karbasi, Masoud, Ali, Mumtaz, Bateni, Sayed M., Jun, Changhyun, Jamei, Mehdi and Yaseen, Zaher Mundher. 2024. "Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition." Alexandria Engineering Journal. 86, pp. 425-442. https://doi.org/10.1016/j.aej.2023.11.061
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao, Hai, Abba, Sani I., Al-Areeq, Ahmed M., Tangang, Fredolin, Samantaray, Sandeep, Sahoo, Abinash, Siqueira, Hugo Valadares, Maroufpoor, Saman, Demir, Vahdettin, Bokde, Neeraj Dhanraj, Goliatt, Leonardo, Jamei, Mehdi, Ahmadianfar, Iman, Bhagat, Suraj Kumar, Halder, Bijay, Guo, Tianli, Helman, Daniel S., Ali, Mumtaz, Sattar, Sabaa, ..., Yaseen, Zaher Mundher. 2024. "Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions ." Engineering Applications of Artificial Intelligence. 129. https://doi.org/10.1016/j.engappai.2023.107559
Adaptive Regularization and Resilient Estimation in Federated Learning
Uddin, Md Palash, Xiang, Yong, Zhao, Yao, Ali, Mumtaz, Zhang, Yushu and Gao, Longxiang. 2024. "Adaptive Regularization and Resilient Estimation in Federated Learning." IEEE Transactions on Services Computing. 17 (4), pp. 1369-1381. https://doi.org/10.1109/TSC.2023.3332703
Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Karimi, Bakhtiar, Jahannemaei, Neshat, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2024. "Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR." Expert Systems with Applications. 237 (Part B). https://doi.org/10.1016/j.eswa.2023.121512
Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study
Ibrahim, Hekmat, Yaseen, Zaher Mundher, Scholz, Miklas, Ali, Mumtaz, Gad, Mohamed, Elsayed, Salah, Khadr, Mosaad, Hussein, Hend, Ibrahim, Hazem H., Eid, Mohamed Hamdy, Kovács, Attila, Péter, Szűcs and Khalifa, Moataz M.. 2023. "Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study." Water. 15 (4). https://doi.org/10.3390/w15040694
A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Sharma, Ekta, Jamei, Mozhdeh, Chu, Xuefeng and Yaseen, Zaher Mundher. 2023. "A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture." Engineering Applications of Artificial Intelligence. 120. https://doi.org/10.1016/j.engappai.2023.105895
Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Chu, Xuefeng, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2023. "Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration." Agricultural Water Management. 290. https://doi.org/10.1016/j.agwat.2023.108604
An ensemble machine learning-based intelligent system for human activity recognition using sensory data
Abdulla, Shahab, Diykh, Mohammed, Siuly, Siuly and Ali, Mumtaz. 2023. "An ensemble machine learning-based intelligent system for human activity recognition using sensory data." Sinha, G.R., Subudhi, Bidyadhar, Fan, Chih-Peng and Nisar, Humaira (ed.) Cognitive Sensing Technologies and Applications. Institution of Engineering and Technology (IET). pp. 119-130
New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes
Ali, Mumtaz, Jamei, Mehdi, Prasad, Ramendra, Karbasi, Masoud, Xiang, Yong, Cai, Borui, Abdulla, Shahab, Farooque, Aitazaz Ahsan and Labban, Abdulhaleem H.. 2023. "New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes." Ecological Indicators. 155. https://doi.org/10.1016/j.ecolind.2023.111030
Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation
Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Abdulla, Shahab, Yaseen, Zaher Mundher and Farooque, Aitazaz A.. 2023. "Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation." Renewable and Sustainable Energy Reviews. 185. https://doi.org/10.1016/j.rser.2023.113645
Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Rai, Priya, Karbasi, Masoud, Farooque, Aitazaz A. and Yaseen, Zaher Mundher. 2023. "Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting." Ecological Indicators. 153. https://doi.org/10.1016/j.ecolind.2023.110478
Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models
Tao, Hai, Al-Sulttani, Ahmed H., Salih, Sinan Q., Mohammed, Mustafa K.A., Khan, Mohammad Amir, Beyaztas, Beste Hamiye, Ali, Mumtaz, Elsayed, Salah, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models." Atmospheric Research. 291. https://doi.org/10.1016/j.atmosres.2023.106815
Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm
Jamei, Mehdi, Ali, Mumtaz, Jun, Changhyun, Bateni, Sayed M., Karbasi, Masoud, Farooque, Aitazaz A. and Yaseen, Zaher Mundher. 2023. "Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm." Atmospheric Pollution Research. 14 (6). https://doi.org/10.1016/j.apr.2023.101752
Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters
Tao, Hai, Jawad, Ali H., Shather, A.H., Al-Khafaji, Zainab Al, Rashid, Tarik A., Ali, Mumtaz, Al-Ansari, Nadhir Al, Marhoon, Haydar Abdulameer, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters." Environment International. 175. https://doi.org/10.1016/j.envint.2023.107931
Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network
Jamei, Mehdi, Ali, Mumtaz, Karimi, Bakhtiar, Karbasi, Masoud, Farooque, Aitataz Ahsan and Yaseen, Zaher Mundher. 2023. "Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network." Process Safety and Environmental Protection. 174, pp. 115-134. https://doi.org/10.1016/j.psep.2023.03.062
Development of neutrosophic cubic hesitant fuzzy exponential aggregation operators with application in environmental protection problems
Rehman, Ateeq Ur, Gulistan, Muhammad, Ali, Mumtaz, M.Al‑Shamiri, Mohammed M. and Abdulla, Shahab. 2023. "Development of neutrosophic cubic hesitant fuzzy exponential aggregation operators with application in environmental protection problems." Scientific Reports. 13, pp. 1-18. https://doi.org/10.1038/s41598-022-22399-3
A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach
Jamei, Mehdi, Karimi, Bakhtiar, Ali, Mumtaz, Alinazari, Fariba, Karbasi, Masoud, Maroufpoor, Eisa and Chu, Xuefeng. 2023. "A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach." Journal of Hydrology. 620 (Part A). https://doi.org/10.1016/j.jhydrol.2023.129402
A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm
Jamei, Mehdi, Karbasi, Masoud, Ali, Mumtaz, Malik, Anurag, Chu, Xuefeng and Yaseen, Zaher Mundher. 2023. "A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm." Expert Systems with Applications. 222. https://doi.org/10.1016/j.eswa.2023.119811
Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach
Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Karbasi, Masoud, Yaseen, Zaher Mundher and Farooque, Aitazaz Ahsan. 2023. "Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach." Engineering Applications of Artificial Intelligence. 121. https://doi.org/10.1016/j.engappai.2023.105984
Designing pentapartitioned neutrosophic cubic set aggregation operator-based air pollution decision-making model
Li, Yi-ming, Khan, Majid, Khurshid, Adnan, Gulistan, Muhammad, Rehman, Ateeq Ur, Ali, Mumtaz, Abdulla, Shahab and Farooque, Aitazaz A.. 2023. "Designing pentapartitioned neutrosophic cubic set aggregation operator-based air pollution decision-making model ." Complex and Intelligent Systems. https://doi.org/10.1007/s40747-023-00971-2
Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Jamei, Mehdi and Yaseen, Zaher Mundher. 2023. "Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting." Renewable Energy. 205, pp. 731-746. https://doi.org/10.1016/j.renene.2023.01.108
An intelligent model involving multi-channels spectrum patterns based features for automatic sleep stage classification
Abdulla, Shahab, Diykh, Mohammed, Siuly, Siuly and Ali, Mumtaz. 2023. "An intelligent model involving multi-channels spectrum patterns based features for automatic sleep stage classification." International Journal of Medical Informatics. 171. https://doi.org/10.1016/j.ijmedinf.2023.105001
Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition
Diykh, Mohammed, Abdulla, Shahab, Deo, Ravinesh C, Siuly, Siuly and Ali, Mumtaz. 2023. "Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition." Computer Methods and Programs in Biomedicine. 229. https://doi.org/10.1016/j.cmpb.2022.107305
A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally
Sultana, Fazeelat, Gulistan, Muhammad, Ali, Mumtaz, Yaqoob, Naveed, Khan, Muhammad, Rashid, Tabasam and Ahmed, Tauseef. 2023. "A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally ." Journal of Ambient Intelligence and Humanized Computing. 14 (10), p. 13139–13159. https://doi.org/10.1007/s12652-022-03772-6
Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Karbasi, Masoud, Rai, Priya and Yaseen, Zaher Mundher. 2023. "Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting." Journal of Hydrology. 617 (Part C). https://doi.org/10.1016/j.jhydrol.2023.129105
Developing a novel hybrid Auto Encoder Decoder Bidirectional Gated Recurrent Unit model enhanced with empirical wavelet transform and Boruta-Catboost to forecast significant wave height
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Abdulla, Shahab, Chu, Xuefeng and Yaseen, Zaher Mundher. 2022. "Developing a novel hybrid Auto Encoder Decoder Bidirectional Gated Recurrent Unit model enhanced with empirical wavelet transform and Boruta-Catboost to forecast significant wave height." Journal of Cleaner Production. 379 (Part 2). https://doi.org/10.1016/j.jclepro.2022.134820
Experimental and computational assessment of wetting pattern for two-layered soil profiles in pulse drip irrigation: Designing a novel optimized bidirectional deep learning paradigm
Jamei, Mehdi, Karimi, Farahnaz, Ali, Mumtaz, Karimi, Bakhtiar, Karbasi, Masoud and Aminpour, Younes. 2022. "Experimental and computational assessment of wetting pattern for two-layered soil profiles in pulse drip irrigation: Designing a novel optimized bidirectional deep learning paradigm." Journal of Hydrology. 614 (Part A), pp. 1-15. https://doi.org/10.1016/j.jhydrol.2022.128496
Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Prasad, Ramendra, Li, Jianxin, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction." Scientific Reports. 12 (1), pp. 1-23. https://doi.org/10.1038/s41598-022-09482-5
Forecasting Daily Flood Water Level Using Hybrid Advanced Machine Learning Based Time‑Varying Filtered Empirical Mode Decomposition Approach
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Prasad, Ramendra, Abdulla, Shahab and Yaseen, Zaher Mundher. 2022. "Forecasting Daily Flood Water Level Using Hybrid Advanced Machine Learning Based Time‑Varying Filtered Empirical Mode Decomposition Approach." Water Resources Management. 36 (12), p. 4637–4676. https://doi.org/10.1007/s11269-022-03270-6
Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Salcedo-sanz, Sancho, Sharma, Ekta and Ali, Mumtaz. 2022. "Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction." Measurement. 202, pp. 1-22. https://doi.org/10.1016/j.measurement.2022.111759
Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors
Ahmed, A. A. Masrur, Sharma, Ekta, Jui, S. Janifer Jabin, Deo, Ravinesh C., Nguyen-Huy, Thong and Ali, Mumtaz. 2022. "Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors." Remote Sensing. 14 (5), pp. 1-24. https://doi.org/10.3390/rs14051136
Air quality monitoring based on chemical and meteorological drivers: Application of a novel data filtering-based hybridized deep learning model
Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Karbasi, Masoud, Sharma, Ekta and Yaseen, Zaher Mundher. 2022. "Air quality monitoring based on chemical and meteorological drivers: Application of a novel data filtering-based hybridized deep learning model." Journal of Cleaner Production. 374, pp. 1-17. https://doi.org/10.1016/j.jclepro.2022.134011
Study on the Development of Neutrosophic Triplet Ring and Neutrosophic Triplet Field
Ali, Mumtaz, Smarandache, Florentin and Khan, Mohsin. 2018. "Study on the Development of Neutrosophic Triplet Ring and Neutrosophic Triplet Field." Mathematics. 6, pp. 1-11. https://doi.org/10.3390/math6040046
Neutrosophic Recommender System for Medical Diagnosis Based on Algebraic Similarity Measure and Clustering
Thanh, Nguyen Dang, Son, Le Hoang and Ali, Mumtaz. 2017. "Neutrosophic Recommender System for Medical Diagnosis Based on Algebraic Similarity Measure and Clustering." 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Naples, Italy 09 - 12 Jul 2017 Piscataway, United States. https://doi.org/10.1109/FUZZ-IEEE.2017.8015387
An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis
Thao, Nguyen Xuan, Ali, Mumtaz and Smarandache, Florentin. 2019. "An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis." Journal of Intelligent and Fuzzy Systems. 36 (1), pp. 189-198. https://doi.org/10.3233/JIFS-181084
Linguistic Approaches to Interval Complex Neutrosophic Sets in Decision Making
Dat, Luu Quoc, Thong, Nguyen Tho, Son, Le Hoang, Ali, Mumtaz, Smarandache, Florentin, Abdel-Basset, Mohamed and Long, Hoang Viet. 2019. "Linguistic Approaches to Interval Complex Neutrosophic Sets in Decision Making." IEEE Access. 7, pp. 38902-38917. https://doi.org/10.1109/ACCESS.2019.2902841
Dynamic interval valued neutrosophic set: Modeling decision making in dynamic environments
Thong, Nguyen Tho, Dat, Luu Quoc, Son, Le Hoang, Hoa, Nguyen Dinh, Ali, Mumtaz and Smarandache, Florentin. 2019. "Dynamic interval valued neutrosophic set: Modeling decision making in dynamic environments." Computers in Industry. 108, pp. 45-52. https://doi.org/10.1016/j.compind.2019.02.009
Fuzzy and neutrosophic modeling for link prediction in social networks
Tuan, Tran Manh, Chuan, Pham Minh, Ali, Mumtaz, Ngan, Tran Thi, Mittal, Mamta and Son, Le Hoang. 2019. "Fuzzy and neutrosophic modeling for link prediction in social networks." Evolving Systems. 10, pp. 629-634. https://doi.org/10.1007/s12530-018-9251-y
Integration of Multiple Models with Hybrid Artificial Neural Network-Genetic Algorithm for Soil Cation-Exchange Capacity Prediction
Shahabi, Mahmood, Ghorbani, Mohammad Ali, Naganna, Sujay Raghavendra, Kim, Sungwon, Hadi, Sinan Jasim, Inyurt, Samed, Farooque, Aitazaz Ahsan and Yaseen, Zaher Mundher. 2022. "Integration of Multiple Models with Hybrid Artificial Neural Network-Genetic Algorithm for Soil Cation-Exchange Capacity Prediction." Complexity. 2022. https://doi.org/10.1155/2022/3123475
Long-term multi-step ahead forecasting of root zone soil moisture in different climates: Novel ensemble-based complementary data-intelligent paradigms
Jamei, Mehdi, Karbasi, Masoud, Malik, Anurag, Jamei, Mozhdeh, Jamei, Mozhdeh, Kisi, Ozgur and Yaseen, Zaher Mundher. 2022. "Long-term multi-step ahead forecasting of root zone soil moisture in different climates: Novel ensemble-based complementary data-intelligent paradigms." Agricultural Water Management. 269. https://doi.org/10.1016/j.agwat.2022.107679
Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection
Jamei, Mehdi, Karbasi, Masoud, Alawi, Omer A., Kamar, Haslinda Mohamed, Khedher, Khaled Mohamed, Abba, S.I. and Yaseen, Zaher Mundher. 2022. "Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection." Sustainable Computing: Informatics and Systems . 35. https://doi.org/10.1016/j.suscom.2022.100721
Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods
Iqbal, Zafar, Shahid, Shamsuddin, Ismail, Tarmizi, Sa’adi, Zulfaqar, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods." Sustainability. 14 (11). https://doi.org/10.3390/su14116620
Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection
Malik, Anurag, Jamei, Mehdi, Ali, Mumtaz, Prasad, Ramendra, Karbasi, Masoud and Yaseen, Zaher Mundher. 2022. "Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection." Agricultural Water Management. 272. https://doi.org/10.1016/j.agwat.2022.107812
Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Xiang, Yong, Ahmadianfar, Iman and Yaseen, Zaher Mundher. 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach ." Applied Energy. 326, pp. 1-24. https://doi.org/10.1016/j.apenergy.2022.119925
Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag and Yaseen, Zaher Mundher. 2022. "Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer." Computers and Electronics in Agriculture. 198, pp. 1-17. https://doi.org/10.1016/j.compag.2022.107121
Fuzzy Equivalence on Standard and Rough Neutrosophic Sets and Applications to Clustering Analysis
Thao, Nguyen Xuan, Son, Le Hoang, Cuong, Bui Cong, Ali, Mumtaz and Lan, Luong Hong. 2018. "Fuzzy Equivalence on Standard and Rough Neutrosophic Sets and Applications to Clustering Analysis." Bhateja, Vikrant, Nguyen, Bao Le, Nguyen, Nhu Gia, Satapathy, Suresh Chandra and Le, Dac-Nhuong (ed.) 4th International Conference on Information Systems Design and Intelligent Applications (INDIA 2017). Da Nang, Vietnam 15 - 17 Jun 2017 Singapore. https://doi.org/10.1007/978-981-10-7512-4_82
Development of data-driven models for wind speed forecasting in Australia
Neupane, Ananta, Raj, Nawin, Deo, Ravinesh and Ali, Mumtaz. 2021. "Development of data-driven models for wind speed forecasting in Australia." Deo, R., Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 143-190
Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions
Tao, Hai, Al-Khafaji, Zainab S., Qi, Chongchong, Zounemat-Kermani, Mohammad, Kisi, Ozgur, Tiyasha, Tiyasha, Chau, Kwok-Wing, Nourani, Vahid, Melesse, Assefa M., Elhakeem, Mohamed, Farooque, Aitazaz Ahsan, Nejadhashemi, A. Pouyan, Khedher, Khaled Mohamed, Alawi, Omer A., Deo, Ravinesh C., Shahid, Shamsuddin, Singh, Vijay P. and Yaseen, Zaher Mundher. 2021. "Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions." Engineering Applications of Computational Fluid Mechanics. 15 (1), pp. 1585-1612. https://doi.org/10.1080/19942060.2021.1984992
Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Sankaran, Adarsh, Deo, Ravinesh C., Xiao, Fuyuan and Zhu, Shuyu. 2021. "Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia." Renewable Energy. 177, pp. 1033-1044. https://doi.org/10.1016/j.renene.2021.06.052
Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition
Huynh, Anh Ngoc-Lan, Deo, Ravinesh C., Ali, Mumtaz, Abdulla, Shahab and Raj, Nawin. 2021. "Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition." Applied Energy. 298, pp. 1-19. https://doi.org/10.1016/j.apenergy.2021.117193
Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks
Ghimire, Sujan, Yaseen, Zaher Mundher, Farooque, Aitazaz A., Deo, Ravinesh C., Zhang, Ji and Tao, Xiaohui. 2021. "Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks." Scientific Reports. 11, pp. 1-26. https://doi.org/10.1038/s41598-021-96751-4
Low cost and centimeter-level global positioning system accuracy using real-time kinematic library and real-time kinematic gpsa
Gianey, Hemant K., Ali, Mumtaz, Vijayakumar, Varadarajan, Sharma, Ashutosh and Kumar, Rajiv. 2021. "Low cost and centimeter-level global positioning system accuracy using real-time kinematic library and real-time kinematic gpsa." Recent Advances in Computer Science and Communications. 14 (2), pp. 360-367. https://doi.org/10.2174/2213275912666190328201322
Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Khan, Mohsin, Farooque, Aitazaz Ahsan, Zong, Tianrui and Yaseen, Zaher Mundher. 2021. "Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology." Energy Reports. 7, pp. 6700-6717. https://doi.org/10.1016/j.egyr.2021.09.113
Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh
Yaseen, Zaher Mundher, Ali, Mumtaz, Sharafati, Ahmad, Al-Ansari, Nadhir and Shahid, Shamsuddin. 2021. "Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh." Scientific Reports. 11 (1), pp. 1-25. https://doi.org/10.1038/s41598-021-82977-9
Multifractal characterization and cross correlations of reference evapotranspiration time series of India
Adarsh, S., Nityanjaly, L. J., Pham, Quoc Bao, Sarang, R., Ali, Mumtaz and Nandhineekrishna, P.. 2021. "Multifractal characterization and cross correlations of reference evapotranspiration time series of India." European Physical Journal: Special Topics. 230 (21-22), pp. 3845-3859. https://doi.org/10.1140/epjs/s11734-021-00325-4
Self-supervised cross-iterative clustering for unlabeled plant disease images
Fang, Uno, Li, J., Lu, X., Gao, Longxiang, Ali, Mumtaz and Xiang, Yong. 2021. "Self-supervised cross-iterative clustering for unlabeled plant disease images." Neurocomputing. 456, pp. 36-48. https://doi.org/10.1016/j.neucom.2021.05.066
Spatiotemporal variability of multifractal properties of fineresolution daily gridded rainfall fields over India
Sankaran, Adarsh, Chavan, Sagar Rohidas, Ali, Mumtaz, Devarajan, Archana Devarajan, Dharan, Drisya Sasi and Khan, Muhammad Ismail. 2021. "Spatiotemporal variability of multifractal properties of fineresolution daily gridded rainfall fields over India." Natural Hazards. 106 (3), pp. 1951-1979. https://doi.org/10.1007/s11069-021-04523-0
Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Li, Ya and Yaseen, Zaher Mundher. 2020. "Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach." Hydrological Sciences Journal. 65 (16), pp. 2693-2708. https://doi.org/10.1080/02626667.2020.1808219
Modeling wheat yield with data-intelligent algorithms: artificial neural network versus genetic programming and minimax probability machine regression
Ali, Mumtaz and Deo, Ravinesh C.. 2020. "Modeling wheat yield with data-intelligent algorithms: artificial neural network versus genetic programming and minimax probability machine regression." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 37-87
Multifractal Cross Correlation Analysis of Agro-Meteorological Datasets (Including Reference Evapotranspiration) of California, United States
Sankaran, A., Krzyszczak, Jaromir, Baranowski, Piotr, Devarajan Sindhu, Archana, Nandhineekrishna Pradeep, Kumar, Lija Jayaprakash, Nityanjali, Thankamani, Vandana and Ali, Mumtaz. 2020. "Multifractal Cross Correlation Analysis of Agro-Meteorological Datasets (Including Reference Evapotranspiration) of California, United States." Atmosphere. 11 (10), pp. 1-24. https://doi.org/10.3390/atmos11101116
Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan
Ali, Mumtaz. 2019. Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/S847-M467
Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Deo, Ravinesh C.. 2020. "Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms." Renewable and Sustainable Energy Reviews. 132. https://doi.org/10.1016/j.rser.2020.110003
Arithmetic Operations of Neutrosophic Sets, Interval Neutrosophic Sets and Rough Neutrosophic Sets
Smarandache, Florentin, Ali, Mumtaz and Khan, Mohsin. 2019. "Arithmetic Operations of Neutrosophic Sets, Interval Neutrosophic Sets and Rough Neutrosophic Sets." Kahraman, Cengiz and Otay, Irem (ed.) Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets. Cham, Switzerland. Springer. pp. 25-42
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517
Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction
Sharafati, Ahmad, Haghbin, Masoud, Aldlemy, Mohammed Suleman, Mussa, Mohamed H., Al Zand, Ahmed W., Ali, Mumtaz, Bhagat, Suraj Kumar, Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2020. "Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction." Applied Sciences. 10 (11), pp. 1-25. https://doi.org/10.3390/app10113811
A double decomposition-based modelling approach to forecast weekly solar radiation
Prasad, Ramendra, Ali, Mumtaz, Xiang, Yong and Khan, Huma. 2020. "A double decomposition-based modelling approach to forecast weekly solar radiation." Renewable Energy. 152, pp. 9-22. https://doi.org/10.1016/j.renene.2020.01.005
M-CFIS-R: Mamdani Complex Fuzzy Inference System with Rule Reduction Using Complex Fuzzy Measures in Granular Computing
Tuan, Tran Manh, Lan, Luong Thi Hong, Chou, Shuo-Yan, Ngan, Tran Thi, Son, Le Hoang, Giang, Nguyen Long and Ali, Mumtaz. 2020. "M-CFIS-R: Mamdani Complex Fuzzy Inference System with Rule Reduction Using Complex Fuzzy Measures in Granular Computing." Mathematics. 8 (5), pp. 1-24. https://doi.org/10.3390/math8050707
Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Yaseen, Z.. 2020. "Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts." Journal of Hydrology. 584, pp. 1-15. https://doi.org/10.1016/j.jhydrol.2020.124647
The Generalized Neutrosophic Cubic Aggregation Operators and Their Application to Multi-Expert Decision-Making Method
Khan, Majid, Gulistan, Muhammad, Ali, Mumtaz and Chammam, Wathek. 2020. "The Generalized Neutrosophic Cubic Aggregation Operators and Their Application to Multi-Expert Decision-Making Method." Symmetry. 12 (4), pp. 1-15. https://doi.org/10.3390/sym12040496
Prediction of evaporation in arid and semi-arid regions: a comparative study using different machine learning models
Yaseen, Zaher Mundher, Al-Juboori, Al-Juboori, Beyaztasc, Ufuk, Al-Ansari, Nadhir, Chau, Kwok-Wing, Qi, Chongchong, Ali, Mumtaz, Salih, Sinan Q. and Shahid, Shamsuddin. 2020. "Prediction of evaporation in arid and semi-arid regions: a comparative study using different machine learning models." Engineering Applications of Computational Fluid Mechanics. 14 (1), pp. 70-89. https://doi.org/10.1080/19942060.2019.1680576
Monthly rainfall forecasting with Markov Chain Monte Carlo simulations integrated with statistical bivariate copulas
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2020. "Monthly rainfall forecasting with Markov Chain Monte Carlo simulations integrated with statistical bivariate copulas." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 89-105
Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms
Ali, Mumtaz, Deo, Ravinesh C., Maraseni, Tek and Downs, Nathan J.. 2019. "Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms." Journal of Hydrology. 576, pp. 164-184. https://doi.org/10.1016/j.jhydrol.2019.06.032
Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition
Ali, Mumtaz and Prasad, Ramendra. 2019. "Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition." Renewable and Sustainable Energy Reviews. 104, pp. 281-295. https://doi.org/10.1016/j.rser.2019.01.014
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
Prasad, Ramendra, Ali, Mumtaz, Kwan, Paul and Khan, Huma. 2019. "Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation." Applied Energy. 236, pp. 778-792. https://doi.org/10.1016/j.apenergy.2018.12.034
Logic connectives of complex fuzzy sets
Ngan, Tran Thi, Lan, Luong Thi Hong, Ali, Mumtaz, Tamir, Dan, Son, Le Hoang, Tuan, Tran Manh, Rishe, Naphtali and Kandel, Abe. 2018. "Logic connectives of complex fuzzy sets." Romanian Journal of Information Science and Technology. 21 (4), pp. 344-357.
A novel approach for fuzzy clustering based on neutrosophic association matrix
Long, Hoang Viet, Ali, Mumtaz, Son, Le Hoang, Khan, Mohsin and Tu, Doan Ngoc. 2019. "A novel approach for fuzzy clustering based on neutrosophic association matrix." Computers and Industrial Engineering. 127, pp. 687-697. https://doi.org/10.1016/j.cie.2018.11.007
Systematic review of decision making algorithms in extended neutrosophic sets
Khan, Mohsin, Son, Le Hoang, Ali, Mumtaz, Chau, Hoang Thi Minh, Na, Nguyen Thi Nhu and Smarandache, Florentin. 2018. "Systematic review of decision making algorithms in extended neutrosophic sets." Symmetry. 10 (8), pp. 1-28. https://doi.org/10.3390/sym10080314
Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
Hou, Muzhou, Zhang, Tianle, Weng, Futian, Ali, Mumtaz, Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2018. "Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model." Energies. 11 (12), pp. 1-19. https://doi.org/10.3390/en11123415
New Soft Set Based Class of Linear Algebraic Codes
Ali, Mumtaz, Khan, Huma, Son, Le Hoang, Smarandache, Florentin and Kandasamy, W. B. Vasantha. 2018. "New Soft Set Based Class of Linear Algebraic Codes." Symmetry. 10 (10), pp. 1-10. https://doi.org/10.3390/sym10100510
H-max distance measure of intuitionistic fuzzy sets in decision making
Ngan, Roan Thi, Son, Le Hoang, Cuong, Bui Cong and Ali, Mumtaz. 2018. "H-max distance measure of intuitionistic fuzzy sets in decision making." Applied Soft Computing. 69, pp. 393-425. https://doi.org/10.1016/j.asoc.2018.04.036
Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: a new hybrid copula-driven approach
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: a new hybrid copula-driven approach." Agricultural and Forest Meteorology. 263, pp. 428-448. https://doi.org/10.1016/j.agrformet.2018.09.002
Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting." Computers and Electronics in Agriculture. 152, pp. 149-165. https://doi.org/10.1016/j.compag.2018.07.013
Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting." Atmospheric Research. 213, pp. 450-464. https://doi.org/10.1016/j.atmosres.2018.07.005
An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index." Atmospheric Research. 207, pp. 155-180. https://doi.org/10.1016/j.atmosres.2018.02.024
Bipolar neutrosophic soft sets and applications in decision making
Ali, Mumtaz, Son, Le Hoang, Deli, Irfan and Tien, Nguyen Dang. 2017. "Bipolar neutrosophic soft sets and applications in decision making." Journal of Intelligent and Fuzzy Systems. 33 (6), pp. 4077-4087. https://doi.org/10.3233/JIFS-17999
Link prediction in co-authorship networks based on hybrid content similarity metric
Chuan, Pham Minh, Son, Le Hoang, Ali, Mumtaz, Khang, Tran Dinh, Huong, Le Thanh and Dey, Nilanjan. 2018. "Link prediction in co-authorship networks based on hybrid content similarity metric." Applied Intelligence. 48 (8), pp. 2470-2486. https://doi.org/10.1007/s10489-017-1086-x
A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures
Ali, Mumtaz, Son, Le Hoang, Thanh, Nguyen Dang and Minh, Nguyen Van. 2018. "A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures." Applied Soft Computing. 71, pp. 1054-1071. https://doi.org/10.1016/j.asoc.2017.10.012
Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices
Ali, Mumtaz, Son, Le Hoang, Khan, Mohsin and Tung, Nguyen Thanh. 2017. "Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices." Expert Systems with Applications. 91, pp. 434-441. https://doi.org/10.1016/j.eswa.2017.09.027
Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making
Ali, Mumtaz, Dat, Luu Quoc, Son, Le Hoang and Smarandache, Florentin. 2018. "Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making." International Journal of Fuzzy Systems. 20 (3), pp. 986-999. https://doi.org/10.1007/s40815-017-0380-4
δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis
Ngan, Roan Thi, Ali, Mumtaz and Son, Le Hoang. 2018. "δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis." Applied Intelligence. 48 (2), pp. 499-525. https://doi.org/10.1007/s10489-017-0986-0
A novel clustering algorithm in a neutrosophic recommender system for medical diagnosis
Thanh, Nguyen Dang, Ali, Mumtaz and Son, Le Hoang. 2017. "A novel clustering algorithm in a neutrosophic recommender system for medical diagnosis." Cognitive Computation. 9 (4), pp. 526-544. https://doi.org/10.1007/s12559-017-9462-8