| 書目名稱 | Time-Series Prediction and Applications |
| 副標(biāo)題 | A Machine Intelligen |
| 編輯 | Amit Konar,Diptendu Bhattacharya |
| 視頻video | http://file.papertrans.cn/926/925560/925560.mp4 |
| 概述 | Proposes generic solutions to the prediction of an economic time-series with alternative formulations using machine learning and type-2 fuzzy sets.Offers original content and a unique presentation sty |
| 叢書名稱 | Intelligent Systems Reference Library |
| 圖書封面 |  |
| 描述 | .This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series.Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at the end of each chapter to the readers’ ability and understanding of the topics covered.. |
| 出版日期 | Book 2017 |
| 關(guān)鍵詞 | Intelligent Systems; Computational Intelligence; Time Series Prediction; Machine Learning; Type-2 Fuzzy |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-54597-4 |
| isbn_softcover | 978-3-319-85435-9 |
| isbn_ebook | 978-3-319-54597-4Series ISSN 1868-4394 Series E-ISSN 1868-4408 |
| issn_series | 1868-4394 |
| copyright | Springer International Publishing Switzerland 2017 |
|Archiver|手機(jī)版|小黑屋|
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