{"title":"基于频率的遗传算法模型降阶方法","authors":"Z. Abo-Hammour, O. Alsmadi, A. Al-Smadi","doi":"10.1109/WOSSPA.2011.5931421","DOIUrl":null,"url":null,"abstract":"A frequency-based model order reduction (MOR) via genetic algorithm (GA) approach is presented in this paper. An exogenous autoregressive model with a smaller dimensionality, which can mimic the full order model, maybe obtained using the GA MOR approach. For a general MOR, the GA predicts the elements of the system state matrix [A] defined in a state space representation along with the elements of the [B] and [C] matrices of the reduced order model. As a frequency-based MOR technique, the GA predicts only the elements of the [B] and [C] matrices of the reduced order model while [A] is set in the modal form. The proposed GA model order reduction approach is compared to recently published work for method evaluation.","PeriodicalId":343415,"journal":{"name":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Frequency-based model order reduction via genetic algorithm approach\",\"authors\":\"Z. Abo-Hammour, O. Alsmadi, A. Al-Smadi\",\"doi\":\"10.1109/WOSSPA.2011.5931421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A frequency-based model order reduction (MOR) via genetic algorithm (GA) approach is presented in this paper. An exogenous autoregressive model with a smaller dimensionality, which can mimic the full order model, maybe obtained using the GA MOR approach. For a general MOR, the GA predicts the elements of the system state matrix [A] defined in a state space representation along with the elements of the [B] and [C] matrices of the reduced order model. As a frequency-based MOR technique, the GA predicts only the elements of the [B] and [C] matrices of the reduced order model while [A] is set in the modal form. The proposed GA model order reduction approach is compared to recently published work for method evaluation.\",\"PeriodicalId\":343415,\"journal\":{\"name\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Systems, Signal Processing and their Applications, WOSSPA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSSPA.2011.5931421\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Systems, Signal Processing and their Applications, WOSSPA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2011.5931421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency-based model order reduction via genetic algorithm approach
A frequency-based model order reduction (MOR) via genetic algorithm (GA) approach is presented in this paper. An exogenous autoregressive model with a smaller dimensionality, which can mimic the full order model, maybe obtained using the GA MOR approach. For a general MOR, the GA predicts the elements of the system state matrix [A] defined in a state space representation along with the elements of the [B] and [C] matrices of the reduced order model. As a frequency-based MOR technique, the GA predicts only the elements of the [B] and [C] matrices of the reduced order model while [A] is set in the modal form. The proposed GA model order reduction approach is compared to recently published work for method evaluation.