A fuzzy based model for rainfall prediction

Author:

Zahran Bilal

Abstract

Of all the current challenges faced by Jordan, the most severe is the inadequacy of the water supply. The country is almost entirely reliant on rainfall, whose pattern, however, is highly variable in terms of its frequency, regularity, and quantity. Evidently, therefore, the ability to anticipate rainfall accurately is critically important for the effective planning and management of water resources in Jordan, and particularly in agricultural areas. Influenced by a range of factors such as temperature, relative humidity, and wind speed, rainfall is a stochastic process. This paper suggests the use of a fuzzy model that draws upon data gathered at 26 stations situated in a range of locations throughout Jordan. The model is capable of forecasting seasonal rainfall relating to a specific station. Its ability to deliver predictions with an acceptable degree of accuracy has been demonstrated, and it can be concluded from this that the fuzzy technique can provide a model that is capable of efficiently forecasting seasonal rainfall.

Publisher

Growing Science

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Communication,Information Systems,Software

Reference1 articles.

1. A fuzzy based model for rainfall prediction;Zahran;International Journal of Data and Network Science,2023

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