Publication: A new technique for maximum load margin estimation and prediction
| dc.citedby | 1 | |
| dc.contributor.author | Aziz N.F.A. | en_US |
| dc.contributor.author | Rahman T.K.A. | en_US |
| dc.contributor.author | Yasin Z.M. | en_US |
| dc.contributor.author | Zakaria Z. | en_US |
| dc.contributor.authorid | 57221906825 | en_US |
| dc.contributor.authorid | 8922419700 | en_US |
| dc.contributor.authorid | 57211410254 | en_US |
| dc.contributor.authorid | 56276791800 | en_US |
| dc.date.accessioned | 2023-05-29T06:01:07Z | |
| dc.date.available | 2023-05-29T06:01:07Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | This paper presents the application of Fast Artificial Immune System (FAIS) for maximum load margin estimation and hybrid Fast Artificial Immune Support Vector Machine (FAISVM) for maximum load margin prediction. The newly developed techniques are marked by its significant fast computation time. A new developed index, Voltage Stability Condition Indicator (VSCI) was used as the fitness function for FAIS and FAISVM in order to evaluate the stability condition of load bus in the system. In FAIS, various mechanisms techniques of AIS were investigated and intensive comparisons were made in order to obtain the best implementation of AIS for maximum load margin estimation. The mechanisms were investigated and compared on three main AIS principles; cloning, mutation and selection. In addition, FAISVM is another new hybrid technique developed for maximum load margin prediction that integrates the application of FAIS and Support Vector Machine (SVM). For validation, FAISVM was compared with Evolutionary Support Vector Machine (ESVM) that uses Evolutionary Programming (EP) as the search algorithm. Based on the results, it shows that FAISVM outperforms ESVM with a higher accuracy prediction value. | en_US |
| dc.description.nature | Final | en_US |
| dc.identifier.epage | 17572 | |
| dc.identifier.issue | 23 | |
| dc.identifier.scopus | 2-s2.0-84953410909 | |
| dc.identifier.spage | 17566 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953410909&partnerID=40&md5=7bf3c59391ca80e03603f465c18e829a | |
| dc.identifier.uri | https://irepository.uniten.edu.my/handle/123456789/22461 | |
| dc.identifier.volume | 10 | |
| dc.publisher | Asian Research Publishing Network | en_US |
| dc.source | Scopus | |
| dc.sourcetitle | ARPN Journal of Engineering and Applied Sciences | |
| dc.title | A new technique for maximum load margin estimation and prediction | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication |