Recursive partitioning algorithm in water quality prediction

Abstract

Water quality prediction is the greatest thing in Health and Family Welfare Department. Potable water consumed by citizens can be safely used for drinking, cooking and washing. The contaminated water affects the public health and mostly affects the infants or utero health. Online water quality prediction tool is very useful to every people especially every mother. In this paper, water quality is predicted by giving the longitude and latitude of one location. Compared with linear model and support vector machine, recursive partitioning method is more practical, reasonable and acceptable. Decision trees have less error rates, high data capabilities and good data quality. The predicting results have shown that this recursive partitioning method could analyze and predict the water quality parameters deeply and precisely. The method proposed in this paper is more accurate and could be the decision support for every citizen and every mother. Online aqua prediction tool reduces the needs of man power and equipments.