Prediction of rainfall based on weather parameter using artificial neural network

Fakroul Ridzuan Hashim, N.G. Nik Daud, K.A. Ahmad, Ja’afar Adnan, Zairi Ismael Rizman

Journal of Fundamental and Applied Sciences · 23 January 2018

In one sentence. Multilayer perceptron trained with Levenberg-Marquardt predicts whether it will rain from temperature, pressure and humidity, reaching 99.75% accuracy.

Abstract

Artificial neural networks which are inspired by the concept of the biological neurons are commonly used in many applications including in the field of weather forecasting.The neural networks approaches have provided an educated process for weather forecasting as well as a viable means of the prediction of raindrop.This paper attempts to determine the suitability and the applicability of artificial neural networks for rain prediction based on temperature, pressure and humidity.Those conditions have been used as input data and solution was classified as percentage of raining.Multilayer perceptron network with two different learning algorithms have been studied.The multilayered perceptron trained using Lavenberg Marquardt algorithm has been proven to produce better results with accuracy percentage (99.75%)as compared to back propagation (94.57%).

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