Fuzzy Model, Neural Network and Empirical Model for the Estimation of Global Solar Radiation for Port-Harcourt, Nigeria

  • Olumide Olufemi Akinnawo Department of Physical and Earth Sciences, Crawford University, Igbesa, Ogun State, Nigeria.
  • Oluwaseun Caleb Adebayo Department of Physics, Federal University of Technology, P.M.B. 704, Akure, Ondo State, Nigeria
  • Abel Giwa Usifo Department of Physical and Earth Sciences, Crawford University, Igbesa, Ogun State, Nigeria.
  • Abiodun Kazeem Ogundele Southwestern University of Nigeria, Okun-Owa, Sagamu-Benin Expressway, Ijebu-Ode, Ogun State, Nigeria.
Keywords: Angstrom model, fuzzy logic system, neural network, solar radiation, temperature

Abstract

The invaluable role of the estimation of global solar radiation in solar engineering systems provides very useful direction for various solar applications. This paper employs the Adaptive Neuro Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and regressive technique for the prediction of global solar radiation(GSR) on horizontal surface using temperature swing and relative humidity as input parameters covering years 1981 to 2005. The performance of the models was tested using statistical indicators such as mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (CC). The results with ANFIS and ANN method provide a relatively better prediction with ANFIS the more preferable.

Published
2020-01-04
How to Cite
Akinnawo, O. O., Adebayo, O. C., Usifo, A. G., & Ogundele, A. K. (2020). Fuzzy Model, Neural Network and Empirical Model for the Estimation of Global Solar Radiation for Port-Harcourt, Nigeria. Theory and Applications of Mathematical Science Vol. 1, 51-59. Retrieved from https://stm1.bookpi.org/index.php/tams-v1/article/view/27
Issue
Theory and Applications of Mathematical Science Vol. 1
Section
Chapters