Water quality estimation and prediction in fuzz Environments using metaheuristic approaches

Abstract

Fresh water is an indispensable element for sustaining life on earth. Rivers are the newlineprimary source of fresh water supply. However, over the past few decades deterioration newlineof water quality (WQ) has been endorsed in key rivers all over the world. Thus, river newlineWQ prediction and assessment has become an essential and alarming issue in order to newlineprotect river s health and boost human development. Quantification of WQ of a river is newlinea complex process and involves huge amount of data, multiple parameters which are newlinestrenuous to interpret and analyze. Recently, Computational Intelligence has become a newlineboon in the field of WQ management because of its ability to handle massive data newlinerapidly and requires few input parameters in comparison to classical deterministic newlinemodels. Accompanying this progress and evolvement of Computational Intelligence, newlinemetaheuristics algorithms especially nature-inspired also become powerful and popular newlinein Computational Intelligence for WQ prediction and estimation. newline