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Rainfall Prediction Using an Optimised Genetic-Artificial Neural Network Model

Publication Type : Journal Article

Publisher : International Journal of Pure and Applied Mathematics

Source : International Journal of Pure and Applied Mathematics , Volume 119, Number 10, p.669-678 (2018)

Url : https://acadpubl.eu/jsi/2018-119-10/articles/10a/60.pdf

Keywords : ANN, GA, Partition around medoids (PAM), Self-Organising maps(SOM)

Campus : Kochi

School : School of Arts and Sciences

Department : Computer Science

Year : 2018

Abstract : In the modern world rainfall is very difficult to predict, because of its non-linearity and complicated happening. So, in order to model and predict advance computing technologies are needed. The objective is to analyse the four-months (June, July, August, and September) of rainfall data of 30 years from 1982-2012 in Goa, India. This paper describes Feed Forward -Back Propagation (FFBP) algorithm to train the networks, and to get optimised results Genetic Algorithm (GA) is used. Promising results are obtained for GA approach than Artificial Neural Network (ANN) alone.

 

Cite this Research Publication : R. Arya and Maya L. Pai, “Rainfall Prediction Using an Optimised Genetic-Artificial Neural Network Model ”, International Journal of Pure and Applied Mathematics , vol. 119, pp. 669-678, 2018.

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