Gongcheng Kexue Yu Jishu/Advanced Engineering Science

Title : Predictive Modelling of Machine Learning-Driven Precipitation Prediction
Maskuri Deepika, P.Honey Diana, Dr.M.Sambasivudu

Abstract :

India is an agrarian nation and its economy is for the foremost portion based upon trim efficiency and precipitation. For analyzing the trim capability, precipitation want is require and vital to all agriculturists. Precipitation Want is the application of science and progression to anticipate the state of the climate. It is essential to completely select the precipitation for compelling utilize of water assets, trim viability and pre organizing of water structures. Utilizing unmistakable information mining procedures it can foresee precipitation. Information mining techniques are utilized to overview the precipitation numerically. This paper centers a number of of the transcendent information mining calculations for precipitation want. Credulous Bayes, K-Nearest Neighbor calculation, Choice Tree, Neural Organize and padded premise are numerous of the calculations compared in this paper. From that comparison, it can analyze which strategy gives superior exactness for

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