Using the artificial neural networks for prediction and validating solar radiation

  • Mohamed Z
N/ACitations
Citations of this article
184Readers
Mendeley users who have this article in their library.

Abstract

The main objective of this paper is to employ the artificial neural network (ANN) models for validating and predicting global solar radiation (GSR) on a horizontal surface of three Egyptian cities. The feedforward backpropagation ANNs are utilized based on two algorithms which are the basic backpropagation (Bp) and the Bp with momentum and learning rate coefficients respectively. The statistical indicators are used to investigate the performance of ANN models. According to these indicators, the results of the second algorithm are better than the other. Also, model (6) in this method has the lowest RMSE values for all cities in this study. The study indicated that the second method is the most suitable for predicting GSR on a horizontal surface of all cities in this work. Moreover, ANN-based model is an efficient method which has higher precision.

Cite

CITATION STYLE

APA

Mohamed, Z. E. (2019). Using the artificial neural networks for prediction and validating solar radiation. Journal of the Egyptian Mathematical Society, 27(1). https://doi.org/10.1186/s42787-019-0043-8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free