Water is one of the most important natural resource after air. In-spite of the fact that most of the surface of of earth is composed of water there is only small part of that water which is usable. This vital natural resource must therefore be used very carefully. Because this river’s water is used for drinking, domestic purposes, irrigation, and aquatic life including fish and fisheries, river quality may be a major concern. In-order to understand the quality of water that whether it clean or not we have to study and analyse various water quality parameters like BOD (Biochemical Oxygen Demand), temperature , pH(Potential of Hydrogen),DO (Dissolved Oxygen), and conductivity and to understand about the quality of water of various rivers of India that whether it is clean or not ,a classification model using three different classifier is presented in the study.The water quality data were classified using the J48, LMT, and Nave Bayes classification algorithm.The WEKA tool was used for analyse the collected data of various rivers then classify as clean or not clean. In this work we have studied 15 papers from various publishers and created a summary to study about how and why the water is classified as clean or not clean using various machine learning algorithms.
Water Quality Analysis of Major Rivers of India Using Machine Learning
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