Artificial Neural Network based computing model for wind speed prediction: A case study of Coimbatore, Tamil Nadu, India

R Kaja Bantha Navas, S Prakash and T Sasipraba

Physica A: Statistical Mechanics and its Applications, 2020, vol. 542, issue C

Abstract: The two main challenges of predicting the wind speed depend on various atmospheric factors and random variables. This paper explores the possibility of developing a wind speed prediction model using different Artificial Neural Networks (ANNs) and Categorical Regression empirical model which could be used to estimate the wind speed in Coimbatore, Tamil Nadu, India using SPSS software. The proposed Neural Network models are tested on real time wind data and enhanced with statistical capabilities. The objective is to predict accurate wind speed and to perform better in terms of minimization of errors using Multi Layer Perception Neural Network (MLPNN), Radial Basis Function Neural Network (RBFNN) and Categorical Regression (CATREG). Results from the paper have shown good agreement between the estimated and measured values of wind speed. According to the result, it can be concluded that ANN model with MLPNN could produce the acceptable prediction of the wind speed for given on wind direction.

Keywords: Wind speed; Forecasting; Neural Network; Multilayer Perceptron; Radial Basis Function; Categorical Regression (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:542:y:2020:i:c:s0378437119318916

DOI: 10.1016/j.physa.2019.123383

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