| 书目名称 | Using Artificial Neural Networks for Timeseries Smoothing and Forecasting | | 副标题 | Case Studies in Econ | | 编辑 | Jaromír Vrbka | | 视频video | | | 概述 | Gives a survey of artificial neural networks that are suitable for timeseries smoothing and forecasting.Offers case studies that can help the users (students, financial experts etc.) to understand the | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets.. | | 出版日期 | Book 2021 | | 关键词 | Artificial Neural Networks; Forecasting; Timeseries Smoothing; Timeseries; Statistic Methods | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-75649-9 | | isbn_softcover | 978-3-030-75651-2 | | isbn_ebook | 978-3-030-75649-9Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 17:52:03
