Analysis of Rain Model for Drought Prone Areas of India for the Year 2023

Anand M Sharan*
Professor, Mechanical Engineering Department, Faculty of Engineering, Memorial University of Newfoundland, ST. John’s, Newfoundland, Canada
*Corresponding Author: Anand M Sharan, Professor, Mechanical Engineering Department, Faculty of Engineering, Memorial University of Newfoundland, ST. John’s, Newfoundland, Canada.

Published: December 19, 2023

DOI: 10.55162/MCAES.06.152

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Abstract  

This data is analysed using four different methods which are: The Time Series method, The Root Mean Square (RMS) method, The Fast Fourier Transform (FFT) method, and the Artificial Neural Network (ANN) method. The Time Series method, The Root Mean Square (RMS) method, The Fast Fourier Transform (FFT) method, and the Artificial Neural Network (ANN) method. The predicted value using each of the methods is the average of these methods.

This predicted value is compared with the actual value. The reason why it is compared with the average value is because rainfall distribution has been found to be having a normal distribution where the mean or the average value has the maximum probability [1].

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