A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture

Article

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
Article Title

A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture

ERA Journal ID32032
Article CategoryArticle
AuthorsJamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Sharma, Ekta, Jamei, Mozhdeh, Chu, Xuefeng and Yaseen, Zaher Mundher
Journal TitleEngineering Applications of Artificial Intelligence
Journal Citation120
Article Number105895
Number of Pages25
Year2023
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN0952-1976
1873-6769
Digital Object Identifier (DOI)https://doi.org/10.1016/j.engappai.2023.105895
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0952197623000799
Abstract

The objective of this study is to develop a novel multi-level pre-processing framework and apply it for multi-step (one and seven days ahead) daily forecasting of Surface soil moisture (SSM) based on the NASA’s Soil Moisture Active Passive (SMAP)-satellite datasets in arid and semi-arid regions of Iran. The framework consists of the Boruta gradient boosting decision tree (Boruta-GBDT) feature selection integrated with the multivariate variational mode decomposition (MVMD) and advanced machine learning (ML) models including bidirectional gated recurrent unit (Bi-GRU), cascaded forward neural network (CFNN), adaptive boosting (AdaBoost), genetic programming (GP), and classical multilayer perceptron neural network (MLP). For this purpose, effective geophysical soil moisture predictors for two arid stations of Khosrowshah and Neyshabur were first filtered among 21 daily input signals from 2015 to 2020 by using the Boruta-GBDT feature selection. The selected signals were then decomposed using the MVMD scheme. In the last pre-processing stage, the most relevant sub-sequences from a large pool in previous process were filtered using the Boruta-GBDT scheme aiming to reduce the computation and enhance the accuracy, before feeding the ML approaches. The comparison of the results from the five hybrid and standalone counterpart models in term of standardized RMSE improvement (SRMSEI) revealed that 𝑀VMD-𝐵G-𝐶FNN for SSM(T+1)|27.13% and SSM (T+7)| 43.55% at Khosrowshah station and SSM(T+1)| 21.16% and SSM (T+7)| 30.10% at Neyshabur station outperformed the other hybrid frameworks,followed by 𝑀VMD-𝐵G-𝐵i−GRU, 𝑀VMD-BG-𝐴daboost , 𝑀VMD-𝐵G-𝐺P, and 𝑀VMD-𝐵G-𝑀LP. The accurately forecasted
SSM data help improve irrigation scheduling, which is of significant importance in water use efficiency and food security.

KeywordsSurface soil moistur, forecasting, Microwave remote sensing,SMAP, Cascaded forward neural network, Bidirectional gated recurrent unit, Boruta-GBDT, Multivariate variational model decomposition
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020461103. Deep learning
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Byline AffiliationsShahid Chamran University of Ahvaz, Iran
UniSQ College
University of Prince Edward Island, Canada
University of Zanjan, Iran
School of Mathematics, Physics and Computing
Ferdowsi University of Mashhad, Iran
North Dakota State University, United States
King Fahd University of Petroleum and Minerals, Saudi Arabia
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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), pp. 1-21. 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
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
Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2019. "Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm." AMSI Optimise 2019. Perth, Australia 17 - 21 Jun 2019 Perth, Australia.
Connecting community online and through partnership: A reflective piece
Pickstone, Leigh, Sharma, Ekta, King, Rachel, Galligan, Linda and Langlands, Trevor. 2022. "Connecting community online and through partnership: A reflective piece." International Journal for Students as Partners. 6 (2), pp. 114-120. https://doi.org/10.15173/ijsap.v6i2.4825
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
Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models
Nguyen-Huy, Thong, Deo, Ravinesh C., Khan, Shahjahan, Devi, Aruna, Adeyinka, Adewuyi Ayodele, Apan, Armando A. and Yaseen, Zaher Mundher. 2022. "Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models." IEEE Access. 10, pp. 45112 -45136. https://doi.org/10.1109/ACCESS.2022.3168322
Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization
Ahmadianfar, Iman, Noori, Ramzia Majeed, Togun, Hussein, Falah, Mayadah W., Homod, Raad Z., Fu, Minglei, Halder, Bijay, Deo, Ravinesh and Yaseen, Zaher Mundher. 2022. "Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization." Knowledge-Based Systems. 250, pp. 1-18. https://doi.org/10.1016/j.knosys.2022.109048
Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study
Halder, Bijay, Bandyopadhyay, Jatisankar, Afan, Haitham Abdulmohsin, Naser, Maryam H., Abed, Salwan Ali, Khedher, Khaled Mohamed, Falih, Khaldoon T., Deo, Ravinesh, Scholz, Miklas and Yaseen, Zaher Mundher. 2022. "Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study." Agronomy. 12 (6), pp. 1-23. https://doi.org/10.3390/agronomy12061268
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
Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model
Ahmed, Abul Abrar Masrur, Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J., Devi, Aruna, Barua, Prabal D. and Yaseen, Zaher M.. 2022. "Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model." Sustainability. 14 (17), pp. 1-27. https://doi.org/10.3390/su141711070
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
Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects
Bhagat, Suraj Kumar, Tiyasha, Tiyasha, Kumar, Adarsh, Malik, Tabarak, Jawad, Ali H., Khedher, Khaled Mohamed, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2022. "Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects." Journal of Environmental Management. 309, pp. 1-16. https://doi.org/10.1016/j.jenvman.2022.114711
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
The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River
Diop, Lamine, Bodian, Ansoumana, Djaman, Koffi, Yaseen, Zaher Mundher, Deo, Ravinesh C., El-Shafie, Ahmed and Brown, Larry C.. 2018. "The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River." Environmental Earth Sciences. 77 (5). https://doi.org/10.1007/s1266
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
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
Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots
Sharma, Ekta, Deo, Ravinesh C., Soar, Jeffrey, Prasad, Ramendra, Parisi, Alfio V. and Raj, Nawin. 2022. "Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots." Atmospheric Environment. 279, pp. 1-13. https://doi.org/10.1016/j.atmosenv.2022.119111
Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables
Jui, S. Janifer Jabin, Ahmed, A. A. Masrur, Bose, Aditi, Raj, Nawin, Sharma, Ekta, Soar, Jeffrey and Chowdhury, Md Wasique Islam. 2022. "Spatiotemporal Hybrid Random Forest Model for Tea Yield Prediction Using Satellite-Derived Variables." Remote Sensing. 14 (3), pp. 1-18. https://doi.org/10.3390/rs14030805
Efficient Heat Transfer Augmentation in Channels with Semicircle Ribs and Hybrid Al2O3-Cu/Water Nanofluids
Togun, Hussein, Homod, Raad Z., Yaseen, Zaher Mundher, Abed, Azher M., Dhabab, Jameel M., Ibrahem, Raed Khalid, Dhahbi, Sami, Rashidi, Mohammad Mehdi, Ahmadi, Goodarz, Yaïci, Wahiba and Mahdi, Jasim M.. 2022. "Efficient Heat Transfer Augmentation in Channels with Semicircle Ribs and Hybrid Al2O3-Cu/Water Nanofluids." Nanomaterials. 12 (15). https://doi.org/10.3390/nano12152720
Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
Tahir, Barzan Hussein, Rashid, Tarik A., Rauf, Hafiz Tayyab, Bacanin, Nebojsa, Chhabra, Amit, Vimal, S. and Yaseen, Zaher Mundher. 2022. "Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem." Computational Intelligence and Neuroscience. 2022. https://doi.org/10.1155/2022/7055910
Natural Time Series Parameters Forecasting: Validation of the Pattern-Sequence-Based Forecasting (PSF) Algorithm; A New Python Package
Shende, Mayur Kishor, Salih, Sinan Q., Bokde, Neeraj Dhanraj, Scholz, Miklas, Oudah, Atheer Y. and Yaseen, Zaher Mundher. 2022. "Natural Time Series Parameters Forecasting: Validation of the Pattern-Sequence-Based Forecasting (PSF) Algorithm; A New Python Package." Applied Sciences. 12 (12). https://doi.org/10.3390/app12126194
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
Coupled data pre-processing approach with data intelligence models for monthly precipitation forecasting
Nikpour, M. R., Abdollahi, S., Sanikhani, H., Raeisi, J. and Yaseen, Z. M.. 2022. "Coupled data pre-processing approach with data intelligence models for monthly precipitation forecasting." International Journal of Environmental Science and Technology. 19 (12), pp. 11919-11934. https://doi.org/10.1007/s13762-022-04395-2
Reference evapotranspiration prediction using high-order response surface method
Keshtegar, Behrooz, Abdullah, Shafika Sultan, Huang, Yuk Feng, Saggi, Mandeep Kaur, Khedher, Khaled Mohamed and Yaseen, Zaher Mundher. 2022. "Reference evapotranspiration prediction using high-order response surface method." Theoretical and Applied Climatology. 148 (1-2), pp. 849-867. https://doi.org/10.1007/s00704-022-03954-4
Mesoporous high-surface-area activated carbon from biomass waste via microwave-assisted-H3PO4 activation for methylene blue dye adsorption: An optimized process
Jawad, Ali H., Malek, Nurul Najwa Abd, Khadiran, Tumirah, ALOthman, Zeid A. and Yaseen, Zaher Mundher. 2022. "Mesoporous high-surface-area activated carbon from biomass waste via microwave-assisted-H3PO4 activation for methylene blue dye adsorption: An optimized process." Diamond and Related Materials. 128. https://doi.org/10.1016/j.diamond.2022.109288
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
Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings
Homod, Raad Z., Togun, Hussein, Hussein, Ahmed Kadhim, Al-Mousawi, Fadhel Noraldeen, Yaseen, Zaher Mundher, Al-Kouz, Wael, Abd, Haider J., Alawi, Omer A., Goodarzi, Marjan and Hussein, Omar A.. 2022. "Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings." Applied Energy. 313. https://doi.org/10.1016/j.apenergy.2022.118863
An innovative clustering technique to generate hybrid modeling of cooling coils for energy analysis: A case study for control performance in HVAC systems
Homod, Raad Z., Togun, Hussein, Ateeq, Adnan A., Al-Mousawi, Fadhel Noraldeen, Yaseen, Zaher Mundher, Al-Kouz, Wael, Hussein, Ahmed Kadhim, Alawi, Omer A., Goodarzi, Marjan and Ahmadi, Goodarz. 2022. "An innovative clustering technique to generate hybrid modeling of cooling coils for energy analysis: A case study for control performance in HVAC systems." Renewable and Sustainable Energy Reviews. 166. https://doi.org/10.1016/j.rser.2022.112676
Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform
Heddam, Salim, Yaseen, Zaher Mundher, Falah, Mayadah W., Goliatt, Leonardo, Tan, Mou Leong, Sa’adi, Zulfaqar, Ahmadianfar, Iman, Saggi, Mandeep, Bhatia, Amandeep and Samui, Pijush. 2022. "Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform." Environmental Science and Pollution Research. 29 (51), pp. 77157-77187. https://doi.org/10.1007/s11356-022-21201-1
Temperature and precipitation trend analysis of the Iraq Region under SRES scenarios during the twenty-first century
Hashim, Bassim Mohammed, Maliki, Ali Al, Alraheem, Esam Abd, Al-Janabi, Ahmed Mohammed Sami, Halder, Bijay and Yaseen, Zaher Mundher. 2022. "Temperature and precipitation trend analysis of the Iraq Region under SRES scenarios during the twenty-first century." Theoretical and Applied Climatology. 148 (3-4), pp. 881-898. https://doi.org/10.1007/s00704-022-03976-y
Delineation of urban expansion and drought-prone areas using vegetation conditions and other geospatial indices
Halder, Bijay, Tiyasha, Tiyasha, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2022. "Delineation of urban expansion and drought-prone areas using vegetation conditions and other geospatial indices." Theoretical and Applied Climatology. 149 (3-4), pp. 1277-1295. https://doi.org/10.1007/s00704-022-04108-2
Investigating the relationship between land alteration and the urban heat island of Seville city using multi-temporal Landsat data
Halder, Bijay, Karimi, Alireza, Mohammad, Pir, Bandyopadhyay, Jatisankar, Brown, Robert D. and Yaseen, Zaher Mundher. 2022. "Investigating the relationship between land alteration and the urban heat island of Seville city using multi-temporal Landsat data." Theoretical and Applied Climatology. 150 (1-2), pp. 613-635. https://doi.org/10.1007/s00704-022-04180-8
The impact of climate change on land degradation along with shoreline migration in Ghoramara Island, India
Halder, Bijay, Ameen, Ameen Mohammed Salih, Bandyopadhyay, Jatisankar, Khedher, Khaled Mohamed and Yaseen, Zaher Mundher. 2022. "The impact of climate change on land degradation along with shoreline migration in Ghoramara Island, India." Physics and Chemistry of the Earth. 126. https://doi.org/10.1016/j.pce.2022.103135
Grasshopper Optimization Algorithm with Crossover Operators for Feature Selection and Solving Engineering Problems
Ewees, Ahmed A., Gaheen, Marwa A., Yaseen, Zaher Mundher Yaseen and Ghoniem, Rania M.. 2022. "Grasshopper Optimization Algorithm with Crossover Operators for Feature Selection and Solving Engineering Problems." IEEE Access. 10, pp. 23304-23320. https://doi.org/10.1109/ACCESS.2022.3153038
Application of the ANOVA method in the optimization of a thermoelectric cooler-based dehumidification system
Eltaweel, Mahmoud, Heggy, Aya H., Yaseen, Zaher Mundher, Alawi, Omer A., Falah, Mayadah W., Hussein, Omar A., Ahmed, Waqar, Homod, Raad Z. and Abdelrazek, Ali H.. 2022. "Application of the ANOVA method in the optimization of a thermoelectric cooler-based dehumidification system." Energy Reports. 8, pp. 10533-10545. https://doi.org/10.1016/j.egyr.2022.08.193
Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt
Elmetwalli, Adel H., Mazrou, Yasser S. A., Tyler, Andrew N., Hunter, Peter D., Elsherbiny, Osama, Yaseen, Zaher Mundher and Elsayed, Salah. 2022. "Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt." Agriculture. 12 (3). https://doi.org/10.3390/agriculture12030332
Households’ perceptions and socio-economic determinants of climate change awareness: Evidence from Selangor Coast Malaysia
Ehsan, Sofia, Begum, Rawshan Ara, Maulud, Khairul Nizam Abdul and Yaseen, Zaher Mundher. 2022. "Households’ perceptions and socio-economic determinants of climate change awareness: Evidence from Selangor Coast Malaysia." Journal of Environmental Management. 316. https://doi.org/10.1016/j.jenvman.2022.115261
Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization
Ahmadianfar, Iman, Shirvani-Hosseini, Seyedehelham, Samadi-Koucheksaraee, Arvin and Yaseen, Zaher Mundher. 2022. "Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization." Environmental Science and Pollution Research. 29 (35), pp. 53456-53481. https://doi.org/10.1007/s11356-022-19300-0
An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction
Ahmadianfar, Iman, Shirvani-Hosseini, Seyedehelham, He, Jianxun He, Samadi-Koucheksaraee, Arvin and Yaseen, Zaher Mundher. 2022. "An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction." Scientific Reports. 12 (1). https://doi.org/10.1038/s41598-022-08875-w
Thermal and Hydraulic Performances of Carbon and Metallic Oxides-Based Nanomaterials
Afan, Haitham Abdulmohsin, Aldlemy, Mohammed Suleman, Ahmed, Ali M., Jawad, Ali H., Naser, Maryam H., Homod, Raad Z., Mussa, Zainab Haider, Abdulkadhim, Adnan Hashim, Scholz, Miklas and Yaseen, Zaher Mundher. 2022. "Thermal and Hydraulic Performances of Carbon and Metallic Oxides-Based Nanomaterials." Nanomaterials. 12 (9). https://doi.org/10.3390/nano12091545
Different TiO2 Phases (Degussa/Anatase) Modified Cross-Linked Chitosan Composite for the Removal of Reactive Red 4 Dye: Box–Behnken Design
Abdulhameed, Ahmed Saud, Jawad, Ali H., Vigneshwaran, Sivakumar, ALOthman, Zeid A. and Yaseen, Zaher Mundher Yaseen. 2022. "Different TiO2 Phases (Degussa/Anatase) Modified Cross-Linked Chitosan Composite for the Removal of Reactive Red 4 Dye: Box–Behnken Design." Journal of Polymers and the Environment. 30 (12), pp. 5084-5099. https://doi.org/10.1007/s10924-022-02568-1
Chitosan/Carbon-Doped TiO2 Composite for Adsorption of Two Anionic Dyes in Solution and Gaseous SO2 Capture: Experimental Modeling and Optimization
Abdulhameed, Ahmed Saud, Jawad, Ali H., Ridwan, Muhammad, Khadiran, Tumirah, Wilson, Lee D. and Yaseen, Zaher Mundher. 2022. "Chitosan/Carbon-Doped TiO2 Composite for Adsorption of Two Anionic Dyes in Solution and Gaseous SO2 Capture: Experimental Modeling and Optimization." Journal of Polymers and the Environment. 30 (11), pp. 4619-4636. https://doi.org/10.1007/s10924-022-02532-z
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/https://doi.org/10.1016/j.agwat.2022.107812
Artificial Intelligence and Clean Air: Development of Novel Algorithms with Machine Learning and Deep Learning
Sharma, Ekta. 2022. Artificial Intelligence and Clean Air: Development of Novel Algorithms with Machine Learning and Deep Learning. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q7q7w
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
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
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
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
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
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
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
Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models
Bayatvarkeshi, Maryam, Bhagat, Suraj Kumar, Mohammadi, Kourosh, Kisi, Ozgur, Farahani, M., Hasani, A., Deo, Ravinesh and Yaseen, Zaher Mundher. 2021. "Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models." Computers and Electronics in Agriculture. 185. https://doi.org/10.1016/j.compag.2021.106158
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 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
Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra, Parisi, Alfio and Raj, Nawin. 2020. "Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks." IEEE Access. 8, pp. 209503-209516. https://doi.org/10.1109/ACCESS.2020.3039002
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
Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration
Goundar, Harshna, Yaseen, Zaher Mundher and Deo, Ravinesh. 2021. "Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 191-232
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
Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction
Nguyen-Huy, Thong, Deo, Ravinesh C., Yaseen, Zaher Mundher, Mushtaq, Shahbaz and Prasad, Ramendra. 2021. "Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 29-47
Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation
Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher. 2021. Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer.
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
Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments
Salih, Sinan Q., Sharafati, Ahmad, Ebtehaj, Isa, Sanikhani, Hadi, Siddique, Ridwan, Deo, Ravinesh C., Bonakdari, Hossein, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2020. "Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments." Hydrological Sciences Journal. 65 (7), pp. 1145-1157. https://doi.org/10.1080/02626667.2020.1734813
Global solar radiation estimation and climatic variability analysis using extreme learning machine based predictive model
Tao, Hai, Sharafati, Ahmad, Mohammed, Achite, Salih, Sinan Q., Deo, Ravinesh C., Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2020. "Global solar radiation estimation and climatic variability analysis using extreme learning machine based predictive model." IEEE Access. 8, pp. 12026-12042. https://doi.org/10.1109/ACCESS.2020.2965303
A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2020. "A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms." Science of the Total Environment. 709, pp. 1-23. https://doi.org/10.1016/j.scitotenv.2019.135934
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
Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses
Deo, Ravinesh C., Yaseen, Zaher Mundher, Al-Ansari, Nadhir, Nguyen-Huy, Thong, Langlands, Trevor and Galligan, Linda. 2020. "Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses." IEEE Access. 8, pp. 136697-136724. https://doi.org/10.1109/ACCESS.2020.3010938
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
Designing a new data intelligence model for global solar radiation prediction: application of multivariate modeling scheme
Tao, Hai, Ebtehaj, Isa, Bonakdari, Hossein, Heddam, Salim, Voyant, Cyril, Al-Ansari, Nadhir, Deo, Ravinesh and Yaseen, Zaheer Mundher. 2019. "Designing a new data intelligence model for global solar radiation prediction: application of multivariate modeling scheme." Energies. 12 (7), pp. 1-24. https://doi.org/10.3390/en12071365
Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models
Kisi, Ozgur, Choubin, Bahram, Deo, Ravinesh C. and Yaseen, Zaheer Mundher. 2019. "Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models." Hydrological Sciences Journal. 64 (10), pp. 1240-1252. https://doi.org/10.1080/02626667.2019.1632460
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
Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches
Maroufpoor, Saman, Sanikhani, Hadi, Kisi, Ozgur, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2019. "Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches." International Journal of Climatology. 39 (8), pp. 3543-3557. https://doi.org/10.1002/joc.6037
An enhanced extreme learning machine model for river flow forecasting: state-of-the-art, practical applications in water resource engineering area and future research direction
Yaseen, Zaher Mundher, Sulaiman, Sadeq Oleiwi, Deo, Ravinesh C. and Chau, Kwok-Wing. 2019. "An enhanced extreme learning machine model for river flow forecasting: state-of-the-art, practical applications in water resource engineering area and future research direction." Journal of Hydrology. 569, pp. 387-408. https://doi.org/10.1016/j.jhydrol.2018.11.069
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
Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach
Yaseen, Zaheer Munder, Tran, Minh Tung, Kim, Sungwon, Bakhshpoori, Taha and Deo, Ravinesh C.. 2018. "Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach." Engineering Structures. 177, pp. 244-255. https://doi.org/10.1016/j.engstruct.2018.09.074
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
Hybrid data intelligent models and applications for water level prediction
Yaseen, Zaher Mundher, Deo, Ravinesh C., Ebtehaj, Isa and Bonakdari, Hossein. 2018. "Hybrid data intelligent models and applications for water level prediction." Kim, Dookie, Roy, Sanjiban Sekhar, Länsivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 121-139
Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors
Sanikhani, Hadi, Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur, Mert, Chian, Mirabbasi, Rasoul, Gavili, Siavash and Yaseen, Zaher Mundher. 2018. "Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors." Computers and Electronics in Agriculture. 152, pp. 242-260. https://doi.org/10.1016/j.compag.2018.07.008
Non-tuned data intelligent model for soil temperature estimation: a new approach
Sanikhani, Hadi, Deo, Ravinesh C., Yaseen, Zaher Mundheer, Eray, Okan and Kisi, Ozgur. 2018. "Non-tuned data intelligent model for soil temperature estimation: a new approach." Geoderma. 330, pp. 52-64. https://doi.org/10.1016/j.geoderma.2018.05.030
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
Application of the hybrid artificial neural network coupled with rolling mechanism and grey model algorithms for streamflow forecasting over multiple time horizons
Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C. and El-Shafie, Ahmed. 2018. "Application of the hybrid artificial neural network coupled with rolling mechanism and grey model algorithms for streamflow forecasting over multiple time horizons." Water Resources Management. 32 (5), pp. 1883-1899. https://doi.org/10.1007/s11269-018-1909-5
Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey
Ghorbani, Mohammad Ali, Deo, Ravinesh C., Karimi, Vahid, Yaseen, Zaher Mundher and Terz, Ozlem. 2018. "Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey." Stochastic Environmental Research and Risk Assessment. 32 (6), pp. 1683-1697. https://doi.org/10.1007/s00477-017-1474-0
Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran
Ghorbani, M. A., Deo, Ravinesh C., Yaseen, Zaher Mundher, Kashani, Mahsa H. and Mohammadi, Babak. 2018. "Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran." Theoretical and Applied Climatology. 133 (3-4), pp. 1119-1131. https://doi.org/10.1007/s00704-017-2244-0
Predicting compressive strength of lightweight foamed concrete using extreme learning machine model
Yaseen, Zaher Mundher, Deo, Ravinesh C., Hilal, Ameer, Abd, Abbas M., Bueno, Laura Cornejo, Salcedo-sanz, Sancho and Nehdi, Moncef L.. 2018. "Predicting compressive strength of lightweight foamed concrete using extreme learning machine model." Advances in Engineering Software. 115, pp. 112-125. https://doi.org/10.1016/j.advengsoft.2017.09.004
Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
Yaseen, Zaher Mundher, Ebtehaj, Isa, Bonakdari, Hossein, Deo, Ravinesh C., Mehr, Ali Danandeh, Mohtar, Wan Hanna Melini Wan, Diop, Lamine, El-Shafie, Ahmed and Singh, Vijay P.. 2017. "Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model." Journal of Hydrology. 554, pp. 263-276. https://doi.org/10.1016/j.jhydrol.2017.09.007
Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA
Yaseen, Zaher Mundher, Ghareb, Mazen Ismaeel, Ebtehaj, Isa, Bonakdari, Hossein, Siddique, Ridwan, Heddam, Sali, Yusif, Ali A. and Deo, Ravinesh. 2018. "Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA." Water Resources Management. 32 (1), pp. 105-122. https://doi.org/10.1007/s11269-017-1797-0
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
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Yaseen, Zaher Mundher, Jaafar, Othman, Deo, Ravinesh C., Kisi, Ozgur, Adamowski, Jan, Quilty, John and El-Shafie, Ahmed. 2016. "Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq." Journal of Hydrology. 542, pp. 603-614. https://doi.org/10.1016/j.jhydrol.2016.09.035
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