Role of Fuzzy logic in drinking ground water assessment

Abstract

In modern era, to solve real world problems or to deal with ambiguous situations, traditional principles and methods are rarely adopted. Scientifically, real world problems are complex and are not well defined. The main reasons of these problems are the uncertainties, interdependencies and situations of elements under consideration. Fuzzy logic may be appropriate to solve such complex problems and it provides an acceptable solution in an ambiguous environment. In other words, using fuzzy logic, a real and clear solution of a problem can be drawn from an ambiguous situation. This principle is called fuzzy logic. Fuzzy logic methodology executes in three steps, fuzzification, inference and defuzzification. It represents a problem in natural and linguistic terms rather than representing the problem by the relationships between crisp values. Fuzzy logic is often used in decision making systems as it can solve complex problems in an easy way. Fuzzy logic plays an important role in solving and analyzing natural and environmental problems. In this research paper the fuzzy logic, supervised and unsupervised fuzzy logic methods, used for drinking groundwater quality and availability assessment, have been reviewed in detail. Supervised fuzzy logic requires a prior knowledge about physical, chemical and biological information of drinking groundwater. Supervised fuzzy logic is a hybrid methodology, which may integrates capability and functionality of Artificial Neural Network. In this methodology working of system can be controlled by user and the result of system depends on internal functioning of Artificial Neural Network. This research paper ensures that how and why fuzzy logic is superior to traditional methods of drinking groundwater quality assessment.