Comparison of Angstrom-Prescott, Multiple Regression and Artificial Neural Network Models for the Estimation of Global Solar Radiation in Warri, Nigeria

Dr. Ibeh G.F

Comparison of Angstrom-Prescott, Multiple Regression and Artificial Neural Network Models for the Estimation of Global Solar Radiation in Warri, Nigeria

Dr. Ibeh Gabriel * § M.Sc, Ph.D.

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§ ebonyi state university

Comparison of Angstrom-Prescott, Multiple Regression and Artificial Neural Network Models for the Estimation of Global Solar Radiation in Warri, Nigeria

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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)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(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.

References

12 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Dr. Ibeh G.F. 2012. "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 - D: Neural & AI GJCST-D Volume 12 (GJCST Volume 12 Issue D11).

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GJCST Volume 12 Issue D11

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

7 Angstrom-Prescott artificial neural networks Multi-layer perceptron multiple regression prediction Troposphere

Classification

GJCST-D Classification I.2.6

Submission ReceivedDecember 12, 2011
Peer Review Double Blind
Handling Editor
Accepted January 3, 2012
Published September 15, 2012

Version of record

v1.2

Issue date

September 15, 2012

Language

English

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Article Matrices

Total Score: 110

Country: Nigeria

Subject: Global Journal of Computer Science and Technology - D: Neural & AI

Authors: Dr. Ibeh G.F, Agbo G.A, Oboma D.N, Ekpe J.E, Odoh S (PhD/Dr. count: 1)

View Count (all-time): 542

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Publish Date: 2012 01, Sun

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Total Views: 2.7K

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