Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Mohd Danish Irfan Mohd Sufian
Universiti Teknologi MARA
Control & Systems Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementation of artificial intelligence for prediction performance of solar thermal system Mohd Danish Irfan Mohd Sufian; Nur Ashida Salim; Hasmaini Mohamad; Zuhaila Mat Yasin
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i3.pp1751-1760

Abstract

A related input parameter is used in this case study to forecast solar thermal systems (STS) capabilities and to compare which artificial neural network (ANN) algorithms and other artificial intelligence (AI) methods have the most reliable predictor for STS performance. In order to gauge the performance of the STS, this research aims to implement AI for predicting STS performance by comparing the ANN technique with other methods. Three different training algorithms which are Levenberg-Marquardt (LM), scaled conjugate gradient (SCG) and Bayesian regularization (BR) are considered in this research. This research will identify acceptable parameters and the best AI technique to use in predicting the STS performance. Previous research on STS demonstrates that the efficiency of STS has been estimated using different input parameters. The results show that the prediction of the LM training algorithm is the best for STS performance.
Co-Authors Hasmaini Mohamad Nur Ashida Salim Zuhaila Mat Yasin