A comprehensive data level analysis for cancer diagnosis on imbalanced data S Fotouhi, S Asadi, MW Kattan Journal of biomedical informatics 90, 2019 | 272 | 2019 |
Hybridization of evolutionary Levenberg–Marquardt neural networks and data pre-processing for stock market prediction S Asadi, E Hadavandi, F Mehmanpazir, MM Nakhostin Knowledge-Based Systems 35, 245-258, 2012 | 229 | 2012 |
A new hybrid artificial neural networks for rainfall–runoff process modeling S Asadi, J Shahrabi, P Abbaszadeh, S Tabanmehr Neurocomputing 121 (9), 470-480, 2013 | 168 | 2013 |
Developing a hybrid intelligent model for forecasting problems: Case study of tourism demand time series. J Shahrabi, E Hadavandi, S Asadi Knowledge-Based Systems 43, 112-122, 2013 | 146 | 2013 |
Flash flood susceptibility mapping using a novel deep learning model based on deep belief network, back propagation and genetic algorithm H Shahabi, A Shirzadi, S Ronoud, S Asadi, BT Pham, F Mansouripour, ... Geoscience Frontiers, 2021 | 120 | 2021 |
Improvement of Bagging performance for classification of imbalanced datasets using evolutionary multi-objective optimization E Roshan, S Asadi Engineering Applications of Artificial Intelligence 87, 1-19, 2020 | 94 | 2020 |
An evolutionary deep belief network extreme learning-based for breast cancer diagnosis S Ronoud, S Asadi Soft Computing 23 (24), 13139–13159, 2019 | 82 | 2019 |
Random forest swarm optimization-based for heart diseases diagnosis S Asadi, E Roshan, MW Kattan Journal of Biomedical Informatics, 2021 | 79 | 2021 |
Can deep learning algorithms outperform benchmark machine learning algorithms in flood susceptibility modeling? BT Pham, C Luu, T Van Phong, PT Trinh, A Shirzadi, S Renoud, S Asadi, ... Journal of Hydrology, 125615, 2021 | 74 | 2021 |
Development of a Reinforcement Learning-based Evolutionary Fuzzy Rule-Based System for Diabetes Diagnosis F Mansouripour, S Asadi Computers in Biology and Medicine 91, 337-352, 2017 | 64 | 2017 |
A new hybrid for improvement of auto-regressive integrated moving average models applying particle swarm optimization S Asadi, A Tavakoli, SR Hejazi Expert Systems with Applications 39 (5), 5332-5337, 2012 | 50 | 2012 |
EMDID: Evolutionary Multi-Objective Discretization for Imbalanced Datasets MH Tahan, S Asadi Information Sciences 432, 442–461, 2018 | 41 | 2018 |
An empowered adaptive neuro-fuzzy inference system using self-organizing map clustering to predict mass transfer kinetics in deep-fat frying of ostrich meat plates MR Amiryousefi, M Mohebbi, F Khodaiyan, S Asadi Computers and electronics in agriculture 76 (1), 89-95, 2011 | 41 | 2011 |
An efficient grouping genetic algorithm for data clustering and big data analysis SH Razavi, EOM Ebadati, S Asadi, H Kaur Computational Intelligence for Big Data Analysis: Frontier Advances and …, 2015 | 39 | 2015 |
MEMOD: a novel multivariate evolutionary multi-objective discretization MH Tahan, S Asadi Soft Computimg 22 (1), 301–323, 2018 | 37 | 2018 |
ACORI: a novel ACO algorithm for Rule Induction S Asadi, J Shahrabi Knowledge-Based Systems 97, 175–187, 2016 | 36 | 2016 |
A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping A Shirzadi, S Asadi, H Shahabi, S Ronoud, JJ Clague, K Khosravi, ... Engineering Applications of Artificial Intelligence 96, 103971, 2020 | 34 | 2020 |
Development of an Evolutionary Fuzzy Expert System for Estimating Future Behavior of Stock Price F Mehmanpazir, S Asadi Journal of Industrial Engineering International 13 (1), 29–46, 2017 | 32 | 2017 |
RipMC: RIPPER for Multiclass Classification S Asadi, J Shahrabi Neurocomputing 191, 19–33, 2016 | 31 | 2016 |
Development of a coupled wavelet transform and evolutionary Levenberg-Marquardt neural networks for hydrological process modeling P Abbaszadeh, A Alipour, S Asadi Computational Intelligence 34 (1), 175-199, 2018 | 30 | 2018 |