WEATHER FORECASTING USING ARTIFICIAL NEURAL NETWORKS AND DATA MINING TECHNIQUES

Abstract

Weather forecasts are made by collecting quantitative data about the current state of the atmosphere and using scientific understanding of atmospheric processes to project how the atmosphere will evolve. Weather prediction is basically based upon the historical time series data. The basic Data mining operations and Numerical methods are employed to get a useful pattern from a huge volume of data set. Different testing and training scenarios are performed to obtain the accurate result. To perform these kinds of predictions we are identifying the datasets. Collection of the data sets of a particular region weather report from 1901 to 2001 with 11 attributes. The collected datasets undergo pre-processing. Then clustering operation, Curve fitting and Extrapolation methods are applied, proceeding with back propagation. The Back propagation and Extrapolation results are compared. The Best future results are predicted