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

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

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...

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Bibliographic Details
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/
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

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