نام و نام خانوادگی حسین موییدی شغل پژوهشگر خارجی تحصیلات دکترای تخصصی / School of Engineering and Technology وبسایت پست الکترونیک Hosseinmoayedi [at] duytan [dot] edu [dot] vn مقاله چاپشده در مجلات علمی مقاله ارائه شده کنفرانسی سخنرانی تدریس در کارگاه کتاب نوآوری جذب گرنت پایان نامه کسب مقام در جشنواره طرح پژوهشی خاتمه یافته فروش محصولات دانش بنیان اثر بدیع و ارزنده هنری تدوین استاندارد عنوانمجله 1 Validation of four optimization evolutionary algorithms combined with artificial neural network (ANN) for landslide susceptibility mapping: A case study of Gilan, Iran Ecological Engineering 2 A novel problem-solving method by multi-computational optimization of artificial neural network for modeling and prediction of the flow erosion processes A novel problem-solving method by multi-computational optimization of artificial neural network for modeling and prediction of the flow erosion processes Engineering Applications of Computational Fluid Mechanics 3 A novel evolutionary combination of Artificial intelligence algorithm and machine learning for landslides susceptibility mapping in the west of IRAN Environmental Science and Pollution Research 4 Multilayer Perceptron and Their Comparison with Two Nature-Inspired Hybrid Techniques of Biogeography-Based Optimization (BBO) and Backtracking Search Algorithm (BSA) for Assessment of Landslide Susceptibility Land 5 Groundwater quality evaluation using hybrid model of the multi-layer perceptron combined with neural-evolutionary regression techniques: case study of Shiraz plain Stochastic Environmental Research and Risk Assessment 6 A novel swarm intelligence: cuckoo optimization algorithm (COA) and SailFish optimizer (SFO) in landslide susceptibility assessment Stochastic Environmental Research and Risk Assessment 7 Novel evolutionary-optimized neural network for predicting landslide susceptibility Environment Development and Sustainability 8 A new combined approach of neural-metaheuristic algorithms for predicting and appraisal of landslide susceptibility mapping Environmental Science and Pollution Research