Utilizing soil characteristics and hybrid machine learning for interpretable potato yield prediction: A study with satin-bowerbird optimization and deep neural network

Article

Karbasi, Masoud, Randhawa, Gurjit S., Farooque, Aitazaz A., Ali, Mumtaz, Jamei, Mehdi, Khosravi, Khabat, Afzaal, Hassan, Malik, Anurag and Zaman, Qamar U.. 2026. "Utilizing soil characteristics and hybrid machine learning for interpretable potato yield prediction: A study with satin-bowerbird optimization and deep neural network." Field Crops Research. 338. https://doi.org/10.1016/j.fcr.2025.110311
Article Title

Utilizing soil characteristics and hybrid machine learning for interpretable potato yield prediction: A study with satin-bowerbird optimization and deep neural network

ERA Journal ID5309
Article CategoryArticle
AuthorsKarbasi, Masoud, Randhawa, Gurjit S., Farooque, Aitazaz A., Ali, Mumtaz, Jamei, Mehdi, Khosravi, Khabat, Afzaal, Hassan, Malik, Anurag and Zaman, Qamar U.
Journal TitleField Crops Research
Journal Citation338
Article Number110311
Number of Pages19
Year2026
PublisherElsevier
Place of PublicationNetherlands
ISSN0378-4290
1872-6852
Digital Object Identifier (DOI)https://doi.org/10.1016/j.fcr.2025.110311
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0378429025005763
Abstract

Context
Yield forecasting is crucial to the agricultural planning enterprise, such as input control, farm logistics and reduction of economic risks. The soils in the Maritime provinces of Canada have a great difference in their properties which affect the productivity of crops. Such variability requires a strong prediction model that could address the different characteristics of soil.
Objective
This research proposal is expected to establish a stable potato yield prediction model based on the soil property data of New Brunswick and Prince Edward Island and determine whether the application of optimization techniques with deep learning can enhance the prediction accuracy over the conventional machine learning approach.
Methods
Soil samples were taken at eight experimental sites in the 2017 and 2018 growing seasons, with 18 soil properties being captured. The feature selection techniques were used to create three input scenarios (Comb1, Comb2, Comb3). To optimize the selection of input variables, a hybrid prediction model, DNN-SBO (Deep Neural Network -Satin Bowerbird Optimization), was suggested and refined with the Boruta feature selection and Best Subset Regression-WASPAS. The performance of the model was tested in comparison with Kernel Ridge Regression (KRR), Elastic Net, K-Nearest Neighbors (KNN) and Support Vector Regression (SVR), on the evaluation metrics of Correlation Coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The model interpretability was done using SHAP (Shapley Additive exPlanation) analysis.
Results and Conclusions
Comb2 was the best input scenario that consisted of Total Base Saturation, Sulfur, Magnesium, Potash, Aluminum, Zinc, Phosphate, Manganese, Organic Matter, Iron, and Copper. DNN-SBO model had the best predictive power with R= 0.903 (train) and RMSE= 4.165 t/ha and MAPE= 6.766 % and R= 0.853(test) and RMSE= 5.522 t/ha and MAPE= 9.707 %. The SHAP analysis has shown that Iron was the most significant predictor (mean SHAP = +5.49), next was Copper, Zinc, Phosphorus, and Organic Matter.
Significance
The paper sheds light on the promise of deep learning that is based on bio-inspired optimization and feature selection techniques in order to achieve a significant increase in crop yield prediction. The findings can lead to the wider use of the similar methods in precision agriculture, which will result in smarter and data-driven farming in variably soiled areas.

KeywordsPotato yield; Machine Learning; Deep Learning; Optimization; SHAP
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020461103. Deep learning
Byline AffiliationsUniversity of Prince Edward Island, Canada
University of Guelph, Canada
School of Business, Law, Humanities and Pathways - Business
Shahid Chamran University of Ahvaz, Iran
Razi University, Iran
Punjab Agricultural University, India
Dalhousie University, Canada
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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
Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach
Khosravi, Khabat, Golkarian, Ali, Melesse, Assefa M. and Deo, Ravinesh C.. 2022. "Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach." Journal of Hydrology. 610, pp. 1-14. https://doi.org/10.1016/j.jhydrol.2022.127963
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