Amr H. El-Shafie

发表

An application of different artificial intelligences techniques for water quality prediction

Ahmed El-Shafie, Ali Najah, Othman A. Karim, 2011 .

Support vector regression-based model for prediction of behavior stone column parameters in soft clay under highway embankment

Ahmed El-Shafie, Amr H. El-Shafie, Qasim A. Aljanabi, 2016, Neural Computing and Applications.

New Evolutionary Algorithm for Optimizing Hydropower Generation Considering Multireservoir Systems

Chiu Chuen Onn, Marlinda Abdul Malek, Amr H. El-Shafie, 2019, Applied Sciences.

Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach

Ahmed El-Shafie, Marlinda Abdul Malek, Amr H. El-Shafie, 2018 .

Augmentation of an artificial neural network and modified stochastic dynamic programing model for optimal release policy

Muhammad Mukhlisin, Othman Jaafar, Amr H. El-Shafie, 2015 .

New Approach: Integrated Risk-Stochastic Dynamic Model for Dam and Reservoir Optimization

Ahmed El-Shafie, Muhammad Mukhlisin, Amr H. El-Shafie, 2014, Water Resources Management.

An augmented Wavelet De-noising Technique with Neuro-Fuzzy Inference System for water quality prediction

Othman A. Karim, Amr H. El-Shafie, Ali Najah Ahmed, 2012 .

Application of artificial neural networks for water quality prediction

Ahmed El-Shafie, Amr H. El-Shafie, Ali A. Najah, 2012, Neural Computing and Applications.

Artificial neural network technique for rainfall forecasting applied to Alexandria, Egypt

Ahmed El-Shafie, Amr H. El-Shafie, Mohd Raihan Taha, 2011 .

Towards a time and cost effective approach to water quality index class prediction

Ahmed El-Shafie, Amr H. El-Shafie, Ali Najah Ahmed, 2019, Journal of Hydrology.

Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies

Ozgur Kisi, Ahmed El-Shafie, Saeed Farzin, 2019, Sustainability.

Performance of ANFIS versus MLP-NN dissolved oxygen prediction models in water quality monitoring

Ahmed El-Shafie, Ali Najah, Othman A. Karim, 2014, Environmental Science and Pollution Research.