Short-Term Rainfall using Logistic Regression Algorithm

Farmers and all peoples are expecting for the good rainfall, for farming and for usage of daily water. But for the past decades, we didn’t get much rainfall and all peoples suffered a lot. So, a work is proposed to predict the rainfall. Rainfall data is collected from the hydrological data to predict the storm warning. This is study as an idea as it consumes the large amount of records from the different various distributed system. Spatial temporal characteristics using a Map Reduce Framework to manage the database. The workload is classified using Support Vector Machine (SVM) is classified for workload. It uses the reduction algorithm for dataset and use for feature selection. Different rainfall concept prediction is executed using the big rainfall data. The impact of the dataset parameters are classified into locally, hourly and overall rainfall storms. The proposed system is deals with hadoop tool for predicting a rainfall data from a large amount of data it has no limitation data in a structure manner. The result will be improve the performance of the proposed system it has more accuracy and efficiency..