{"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}
引用次数: 5
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.
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