Comparison of Angstrom-Prescott, Multiple Regression and Artificial Neural Network Models for the Estimation of Global Solar Radiation in Warri, Nigeria
Keywords:
Artificial neural networks, multiple regression, Angstrom-Prescott, prediction, troposphere, Multi-layer perceptron7
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.
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Published
2012-05-15
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Copyright (c) 2012 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.