Hybrid Soft Computing Approach for Determining Water Quality Indicator: Euphrates River

• Main Authors: Jing, Li, Husam Ali , Abdulmohsin, Samer Sami , Hasan, Li , Kaiming, Belal , Al-Khateeb, Mazen Ismaeel, Ghareb, Mohammed, Muamer N.
• Format: Article
• Language: English; English
• Published: Springer 2017
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/18339/1/Hybrid%20soft%20computing%20approach%20for%20determining%20water%20quality%20indicator-%20Euphrates%20River.pdf; http://umpir.ump.edu.my/id/eprint/18339/2/Hybrid%20soft%20computing%20approach%20for%20determining%20water%20quality%20indicator-%20Euphrates%20River%201.pdf; http://umpir.ump.edu.my/id/eprint/18339/; https://link.springer.com/article/10.1007/s00521-017-3112-7

Recent approaches toward solving the regression problems which are characterized by dynamic and nonlinear pattern such as machine learning modeling (including artificial intelligence (AI) approaches) have proven to be useful and successful tools for prediction. Approaches that integrate predictive m...