|Publication type:||Conference paper|
|Type of review:||Peer review (abstract)|
|Title:||Echo state network with chaos noise for time series prediction|
|Proceedings:||Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications|
|Conference details:||International Symposium on Nonlinear Theory and its Applications (NOLTA), Okinawa, Japan, 16–19 November 2020|
|Subjects:||Time series prediction; Echo state network|
|Subject (DDC):||006: Special computer methods|
|Abstract:||In this study, performance of chaos noise injected to Echo State Network for time series prediction is investigated. For the evaluation of the chaos noise, two parameters of the logistic map are selected to produce different features as intermittency chaos and fully developed chaos. By computer simulations, it is confirmed that the three-periodic intermittency chaos noise is better perfor- mance than the fully developed chaos noise for time series prediction.|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||Life Sciences and Facility Management|
|Organisational Unit:||Institute of Computational Life Sciences (ICLS)|
|Appears in collections:||Publikationen Life Sciences und Facility Management|
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