Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms

Electric Machines and Power Systems

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Main Authors: Chang, C.S., Wenquan, J.
Other Authors: ELECTRICAL ENGINEERING
Format: Article
Published: 2014
Online Access:http://scholarbank.nus.edu.sg/handle/10635/62030
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Institution: National University of Singapore
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spelling sg-nus-scholar.10635-620302015-03-14T09:49:25Z Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms Chang, C.S. Wenquan, J. ELECTRICAL ENGINEERING Electric Machines and Power Systems 27 11 1161-1170 EMPSD 2014-06-17T06:46:39Z 2014-06-17T06:46:39Z 1999-11 Article Chang, C.S.,Wenquan, J. (1999-11). Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms. Electric Machines and Power Systems 27 (11) : 1161-1170. ScholarBank@NUS Repository. 0731356X http://scholarbank.nus.edu.sg/handle/10635/62030 NOT_IN_WOS Scopus
institution National University of Singapore
building NUS Library
country Singapore
collection ScholarBank@NUS
description Electric Machines and Power Systems
author2 ELECTRICAL ENGINEERING
author_facet ELECTRICAL ENGINEERING
Chang, C.S.
Wenquan, J.
format Article
author Chang, C.S.
Wenquan, J.
spellingShingle Chang, C.S.
Wenquan, J.
Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms
author_sort Chang, C.S.
title Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms
title_short Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms
title_full Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms
title_fullStr Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms
title_full_unstemmed Determination of worst-case capacitor-switching overvoltage of MRT system using genetic algorithms
title_sort determination of worst-case capacitor-switching overvoltage of mrt system using genetic algorithms
publishDate 2014
url http://scholarbank.nus.edu.sg/handle/10635/62030
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