Abstract
At present, soft computing technology is the latest, most challenging technology used in prediction analysis of weather parameters. Therefore, the accuracy of the prediction in the area of rainfall analysis is very important. However, present methods in predicting rainfalls have less accuracy. In many cases, weather prediction models function poorly. Machine Learning methods ignore the effect of physical factors that make rainfall forecasting. It improves the accuracy of rainfall prediction and analysis and aims to predict rainfall with the related air density, relative humidity and temperature parameters. The most recent advanced remote sensing techniques with Artificial Neural Network model and Fuzzy Logic Control (FLC) associated with big data Assisted Integrated Routing and Surplus Memory (BIRSM) model has been developed with the available India Meteorological Department (IMD) data for the year from to Data preprocessing techniques are applied to the volume of available data. An appropriate and error-reducing evaluation for rainfall prediction is performed in combination with the proposed BIRSM model and Artificial Neural Network. Accurate and time series prediction can be very helpful for agriculture and flood management etc.
Published Version
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