A Review Of Soft Computing Techniques In Modelling The Water Quality Of Rivers

Document Type : Primary Research paper

Authors

1 Computer Science & Information Technology, Mahatma Jyotibha Phule Rohilkhand University, Bareilly, U.P. India

2 Deptt. Of Environment Sci, Gurukul Kangri University, Haridwar, Uttarakhand, India

3 Deptt. Of Computer Science, Uttarakhand Open University, Uttarakhand, India

4 Department of CSE, BT-Kumoun Institute of Technology, Dwarahat, Almora

Abstract

Soft Computing is one of the modern approach to develop various computational intelligence models for real life problems which are much complex and nonlinear like environmental problems. These methods utilizes nature inspired thoughts for implementing a sort of functional solutions for the complex computational problems. The Water Quality (WQ) modeling, assessment and forecasting are very interesting as well as challenging mission for water managing organizations due to the complex and nonlinear relationships between the parameters responsible for determining water quality. The main focus of this paper is to perform a comprehensive literature survey of various researches done across all around by different researchers on the application of soft computing techniques like fuzzy logic, neural network, support vector machine, neuro-fuzzy and genetic algorithms for modelling and predicting the water quality variables. The review of literature resulted in a conclusion that various soft computing techniques have become perceptible choice for researchers to solve majority of issues based on environmental problems. These methods proved to be highly proficient in water quality modelling based problems. Also, this study leads to one more conclusion that these biologically inspired techniques have ample scope in forecasting domain and because of their ability to handle imprecise data these can be applied to solve problems from other domains in an effective manner with.

Keywords

Int. J. of Aquatic Science
Volume 12, Issue 2 - Serial Number 2
June 2021
Pages 4576-4587

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