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Time Series Analysis of Weather Data Using Weka

M. Gayathridevi

Abstract


Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. Time series prediction plays an important role in the field of business such as stock market and exchange, weather prediction, forest fire prediction, rainfall prediction. Based on the time series analysis of the particular data which has been collected from the several fields in order to avoid risks in the future. In this paper, we predict the Time series analysis on Weather dataset. For that, we propose a better preprocessing approach, united with two sets of the process that can handle different types of Time series analysis. We insist that the usage of the supervised method attributes to train the Time series analysis detection model, which will increase the accuracy by at least 5% than the state-of-art approaches.

 


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