dc.contributor.author | Golovko, Vladimir | |
dc.contributor.author | Savitsky, Yury | |
dc.coverage.spatial | Minsk | ru_RU |
dc.date.accessioned | 2023-11-16T12:45:08Z | |
dc.date.available | 2023-11-16T12:45:08Z | |
dc.date.issued | 2001 | |
dc.identifier.citation | Golovko, V. Neural Networks for Chaotic Time Series Forecasting / Vladimir Golovko, Yury Savitsky // The 2nd International Conference on Neural Networks and Artificial Intelligence : proceedings, Minsk, October 2–5, 2001 / Belarusian State University of Informatics and Radioelectronicsb ; ed.: Rauf Kh. Sadykhov [et al.]. – Minsk, 2001. – P. 70–74 : il. – Bibliogr.: p. 74 (10 titles). | ru_RU |
dc.identifier.uri | https://rep.bstu.by/handle/data/37115 | |
dc.description | Головко Владимир Адамович, Савицкий Юрий Викторович. Нейронные сети для прогнозирования хаотических временных рядов | ru_RU |
dc.description.abstract | This paper examines neural network in order to predict behavior o f chaotic systems. The prediction is performed both on the level o f emergent structures and on the level o f individual data points. The network is tested using the Henon and Lorenz chaotic time series. The results o f experiments and future directions are discussed. | ru_RU |
dc.language.iso | en | ru_RU |
dc.publisher | BSUIR | ru_RU |
dc.subject | chaotic Time Series | ru_RU |
dc.subject | хаотический временной ряд | ru_RU |
dc.subject | multilayer Neural Network | ru_RU |
dc.subject | многослойная нейронная Сеть | ru_RU |
dc.subject | horizon of Predictionc | ru_RU |
dc.subject | горизонт прогнозирования | ru_RU |
dc.title | Neural Networks for Chaotic Time Series Forecasting | ru_RU |
dc.title.alternative | Нейронные сети для прогнозирования хаотических временных рядов | ru_RU |
dc.type | Статья (Article) | ru_RU |