Abstract

In this paper, the application of artificial neural network, Angstrom-Prescott and multiple regressions models to study the estimation of global solar radiation in Warri, Nigeria for a time period of seventeen years were carried out. Our study based on Multi-Layer Perceptron (MLP) of artificial neural network was trained and tested using seventeen years (1991-2007) meteorological data. The error results and statistical analysis shows that MLP network has the minimum forecasting error and can be considered as a better model to estimate global solar radiation in Warri compare to the estimation from multiple regressions and Angstrom-Prescott models.

How to Cite
IBEH G.F, AGBO G.A, OBOMA D.N, EKPE J.E, ODOH S, Dr.. Comparison of Angstrom-Prescott, Multiple Regression and Artificial Neural Network Models for the Estimation of Global Solar Radiation in Warri, Nigeria. Global Journal of Computer Science and Technology, [S.l.], sep. 2012. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/288>. Date accessed: 19 jan. 2021.