Economic growth forecasting by artificial neural network with extreme learning machine based on trade, import and export parameters. - Svetlana Sokolov Mladenovic; Milos Milovancevic; Igor Mladenovic; Meysam Alizamir (Comput. Hum. Behav., 2016)

Solar Radiation Estimation in Mediterranean Climate by Weather Variables Using a Novel Bayesian Model Averaging and Machine Learning Methods. - Özgür Kisi; Meysam Alizamir; Slavisa Trajkovic; Jalal Shiri; Sungwon Kim (Neural Process. Lett., 2020)

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)

Drought modelling by standard precipitation index (SPI) in a semi-arid climate using deep learning method: long short-term memory. - Alireza Docheshmeh Gorgij; Meysam Alizamir; Özgür Kisi; Ahmed El-Shafie 001 (Neural Comput. Appl., 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)

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)