Optimization of cable fault recognition system using particle swarm optimization
In this paper, a Partial Discharge (PD) based cable fault recognition system has been constructed using Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference System (ANFIS). The cable fault recognition system can perform well under noise free condition but...
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World Academy of Research in Science and Engineering
2023
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| author | Raymond W.J.K. Jing C.H. Kuan T.M. |
| author2 | 55193255600 |
| author_facet | 55193255600 Raymond W.J.K. Jing C.H. Kuan T.M. |
| author_sort | Raymond W.J.K. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In this paper, a Partial Discharge (PD) based cable fault recognition system has been constructed using Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference System (ANFIS). The cable fault recognition system can perform well under noise free condition but endures performance deterioration when PD noise contamination is present. Particle Swarm Optimization (PSO) was used to enhance the performance of classifiers under noise contamination. A performance review has been done to compare the optimized and unoptimized cable fault recognition under noise contamination. Results show that PSO optimized cable fault recognition systems perform better compared to unoptimized cable fault recognition systems. Among the optimized cable fault recognition systems, ANN outperforms SVM and ANFIS. � 2020, World Academy of Research in Science and Engineering. All rights reserved. |
| format | Article |
| id | my.uniten.dspace-25661 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | World Academy of Research in Science and Engineering |
| record_format | dspace |
| spelling | my.uniten.dspace-256612023-05-29T16:12:23Z Optimization of cable fault recognition system using particle swarm optimization Raymond W.J.K. Jing C.H. Kuan T.M. 55193255600 57219417197 49561583600 In this paper, a Partial Discharge (PD) based cable fault recognition system has been constructed using Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference System (ANFIS). The cable fault recognition system can perform well under noise free condition but endures performance deterioration when PD noise contamination is present. Particle Swarm Optimization (PSO) was used to enhance the performance of classifiers under noise contamination. A performance review has been done to compare the optimized and unoptimized cable fault recognition under noise contamination. Results show that PSO optimized cable fault recognition systems perform better compared to unoptimized cable fault recognition systems. Among the optimized cable fault recognition systems, ANN outperforms SVM and ANFIS. � 2020, World Academy of Research in Science and Engineering. All rights reserved. Final 2023-05-29T08:12:22Z 2023-05-29T08:12:22Z 2020 Article 10.30534/ijeter/2020/2381.12020 2-s2.0-85092674088 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092674088&doi=10.30534%2fijeter%2f2020%2f2381.12020&partnerID=40&md5=8b9881be26b87d4c29566537ed325cf6 https://irepository.uniten.edu.my/handle/123456789/25661 8 1 Special Issue 1 23 147 152 All Open Access, Bronze World Academy of Research in Science and Engineering Scopus |
| spellingShingle | Raymond W.J.K. Jing C.H. Kuan T.M. Optimization of cable fault recognition system using particle swarm optimization |
| title | Optimization of cable fault recognition system using particle swarm optimization |
| title_full | Optimization of cable fault recognition system using particle swarm optimization |
| title_fullStr | Optimization of cable fault recognition system using particle swarm optimization |
| title_full_unstemmed | Optimization of cable fault recognition system using particle swarm optimization |
| title_short | Optimization of cable fault recognition system using particle swarm optimization |
| title_sort | optimization of cable fault recognition system using particle swarm optimization |
| url_provider | http://dspace.uniten.edu.my/ |