Fuzzy Neural Network (EFuNN) for Modelling Dissolved Oxygen Concentration (DO). - Salim Heddam (Intelligence Systems in Environmental Management, 2016)

Modeling daily dissolved oxygen concentration using modified response surface method and artificial neural network: a comparative study. - Behrooz Keshtegar; Salim Heddam (Neural Comput. Appl., 2018)

Modelling daily soil temperature by hydro-meteorological data at different depths using a novel data-intelligence model: deep echo state network model. - Meysam Alizamir; Sungwon Kim; Mohammad Zounemat-Kermani; Salim Heddam; Amin Hasanalipour Shahrabadi; Bahram Gharabaghi (Artif. Intell. Rev., 2021)

Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms. - Rana Muhammad Adnan; Reham R. Mostafa; Abu Reza Md. Towfiqul Islam; Özgür Kisi; Alban Kuriqi; Salim Heddam (Comput. Electron. Agric., 2021)

Groundwater level prediction using machine learning models: A comprehensive review. - Hai Tao; Mohammed Majeed Hameed; Haydar Abdulameer Marhoon; Mohammad Zounemat-Kermani; Salim Heddam; Sungwon Kim; Sadeq Oleiwi Sulaiman; Mou Leong Tan; Zulfaqar Sa'adi; Ali Danandeh Mehr; Mohammed Falah Allawi; Sani Isah Abba; et al. (Neurocomputing, 2022)

Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: Long short-term memory (LSTM) network coupled with wavelet transform. - Meysam Alizamir; Jalal Shiri; Ahmad Fakheri Fard; Sungwon Kim; Alireza Docheshmeh Gorgij; Salim Heddam; Vijay P. Singh (Eng. Appl. Artif. Intell., 2023)

Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study. - Rana Muhammad Adnan; Barenya Bikash Hazarika; Deepak Gupta 004; Salim Heddam; Özgür Kisi (Neural Comput. Appl., 2023)

River water temperature prediction using hybrid machine learning coupled signal decomposition: EWT versus MODWT. - Salim Heddam; Khaled Merabet; Salah Difi; Sungwon Kim; Mariusz Ptak; Mariusz Sojka; Mohammad Zounemat-Kermani; Özgür Kisi (Ecol. Informatics, 2023)

New formulation for predicting total dissolved gas supersaturation in dam reservoir: application of hybrid artificial intelligence models based on multiple signal decomposition. - Salim Heddam; Ahmed M. Al-Areeq; Mou Leong Tan; Iman Ahmadianfar; Bijay Halder; Vahdettin Demir; Huseyin Cagan Kilinc; Sani Isah Abba; Atheer Y. Oudah; Zaher Mundher Yaseen (Artif. Intell. Rev., 2024)

Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge-Kutta with Aquila Optimizer. - Rana Muhammad Adnan; Wang Mo; Ahmed A. Ewees; Salim Heddam; Özgür Kisi; Mohammad Zounemat-Kermani (Int. J. Comput. Intell. Syst., 2024)

Enhancing Pan evaporation predictions: Accuracy and uncertainty in hybrid machine learning models. - Khabat Khosravi; Aitazaz A. Farooque; Amir Naghibi; Salim Heddam; Ahmad Sharafati; Javad Hatamiafkoueieh; Soroush Abolfathi (Ecol. Informatics, 2025)

River total dissolved gas prediction using a hybrid greedy-stepwise feature selection and bidirectional long short-term memory model. - Khabat Khosravi; Salim Heddam; Changhyun Jun 001; Sayed M. Bateni; Dongkyun Kim; Essam Heggy (Ecol. Informatics, 2025)

An efficient data fusion model based on Bayesian model averaging for robust water quality prediction using deep learning strategies. - Meysam Alizamir; Kayhan Moradveisi; Kaywan Othman Ahmed; Jamil Bahrami; Sungwon Kim; Salim Heddam (Expert Syst. Appl., 2025)

Enhancing formation bulk density prediction while drilling using mud logging data and interpretable boosting machine learning. - Ayoub Boutaghane; Ouafi Ameur-Zaimeche; Salim Heddam; Rabah Kechiched; Nasreddine Tahar-Belkacem; Abdelhamid Ouladmansour; Watheq J. Al-Mudhafar; David A. Wood 003 (Earth Sci. Informatics, 2025)

Predicting water quality variables using gradient boosting machine: global versus local explainability using SHapley Additive Explanations (SHAP). - Khaled Merabet; Fabio Di Nunno; Francesco Granata; Sungwon Kim; Rana Muhammad Adnan; Salim Heddam; Özgür Kisi; Mohammad Zounemat-Kermani (Earth Sci. Informatics, 2025)

Enhancing chlorophyll-a predictions using optimal machine learning models and field spectral reflectance. - Mona Allam; Lifu Zhang; Xuejian Sun; Ozgur Kisi; Nand Lal Kushwaha; Liu Yongxin; Massimo Menenti; Salim Heddam (Earth Sci. Informatics, 2025)