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Groundwater Quality Assessment:A Review on Traditional and Soft Computing Approaches


Affiliations
1 Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India
2 Department of Chemistry, Gurukula Kangri Vishwavidyalaya, Haridwar, India
 

Groundwater is indispensable natural resource for survival of human. It is a factor that comprehensively influences the socio-economic growth of any country. Due to uncertainties, interdependencies of parameters and situations of elements under consideration, groundwater quality assessment is a complex real world problem. In modern epoch of research, to solve real world problems or to handle ambiguous situations, traditional principles and approaches are hardly implemented. Soft computing may be appropriate to solve such complex problems and it provides an acceptable solution in an ambiguous environment. Artificial nervous system is helpful in learning and modeling non-linear and complex relationships found in groundwater quality assessment because many relationships between input and output are complex as well as non-linear. Fuzzy logic requires prior knowledge of physical, chemical and biological information about groundwater. It reduces the errors in the procedures used to solve the real world problem and gives accurate result considering hidden relationships or patterns between input and output. Genetic algorithm has been used to select the best result among available results of the groundwater quality. It chooses the best result according to the principles of genetics. In general, it is used to present high-quality solutions for adaptation and search problems. The objective of this research paper is to analyze the qualities of different groundwater quality estimation methods.

Keywords

Groundwater Quality Assessment, Soft Computing, Artificial Neural Network, Fuzzy Logic, Traditional Methods.
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  • Groundwater Quality Assessment:A Review on Traditional and Soft Computing Approaches

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Authors

Shwetank
Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India
Suhas
Department of Chemistry, Gurukula Kangri Vishwavidyalaya, Haridwar, India
Jitendra Kumar Chaudhary
Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, India

Abstract


Groundwater is indispensable natural resource for survival of human. It is a factor that comprehensively influences the socio-economic growth of any country. Due to uncertainties, interdependencies of parameters and situations of elements under consideration, groundwater quality assessment is a complex real world problem. In modern epoch of research, to solve real world problems or to handle ambiguous situations, traditional principles and approaches are hardly implemented. Soft computing may be appropriate to solve such complex problems and it provides an acceptable solution in an ambiguous environment. Artificial nervous system is helpful in learning and modeling non-linear and complex relationships found in groundwater quality assessment because many relationships between input and output are complex as well as non-linear. Fuzzy logic requires prior knowledge of physical, chemical and biological information about groundwater. It reduces the errors in the procedures used to solve the real world problem and gives accurate result considering hidden relationships or patterns between input and output. Genetic algorithm has been used to select the best result among available results of the groundwater quality. It chooses the best result according to the principles of genetics. In general, it is used to present high-quality solutions for adaptation and search problems. The objective of this research paper is to analyze the qualities of different groundwater quality estimation methods.

Keywords


Groundwater Quality Assessment, Soft Computing, Artificial Neural Network, Fuzzy Logic, Traditional Methods.

References