{"title":"非线性动态系统辨识","authors":"V. Shopov, V. Markova","doi":"10.1109/InfoTech.2019.8860871","DOIUrl":null,"url":null,"abstract":"The behaviour of non-linear dynamic systems is studied. In this paper, the authors investigate the modelling and prediction abilities of a Recurrent Neural Network, Long Short Term Memory and Gated Recurrent Unit networks. The the input data sets has a chaotic nature. The effectiveness of all networks in modelling the several chaotic attractors is studied. And a comparison of their prediction quality is made.","PeriodicalId":179336,"journal":{"name":"2019 International Conference on Information Technologies (InfoTech)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Identification of Non-linear Dynamic System\",\"authors\":\"V. Shopov, V. Markova\",\"doi\":\"10.1109/InfoTech.2019.8860871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The behaviour of non-linear dynamic systems is studied. In this paper, the authors investigate the modelling and prediction abilities of a Recurrent Neural Network, Long Short Term Memory and Gated Recurrent Unit networks. The the input data sets has a chaotic nature. The effectiveness of all networks in modelling the several chaotic attractors is studied. And a comparison of their prediction quality is made.\",\"PeriodicalId\":179336,\"journal\":{\"name\":\"2019 International Conference on Information Technologies (InfoTech)\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Information Technologies (InfoTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/InfoTech.2019.8860871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Information Technologies (InfoTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/InfoTech.2019.8860871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The behaviour of non-linear dynamic systems is studied. In this paper, the authors investigate the modelling and prediction abilities of a Recurrent Neural Network, Long Short Term Memory and Gated Recurrent Unit networks. The the input data sets has a chaotic nature. The effectiveness of all networks in modelling the several chaotic attractors is studied. And a comparison of their prediction quality is made.
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