| 書目名稱 | Uncertainty Forecasting in Engineering | | 編輯 | Bernd M?ller,Uwe Reuter | | 視頻video | http://file.papertrans.cn/942/941088/941088.mp4 | | 概述 | Fuzzy time series can be applied in many fields in engineering like environmental engineering or civil engineering.Two simulation-based important forecasting strategies are explained: forecasting base | | 圖書封面 |  | | 描述 | Forecasting is fascinating. Who wouldn’t like to cast a glimpse into the future? Far removed from metaphysics, mathematical methods such as time-lapse techniques, time series or arti?cial neural netwoks o?er a rational means of achieving this. A precondition for the latter is the availability of a sequence of observed values from the past whose temporal classi?cation permits the deduction of attributes necessary for forecasting purposes. The subject matter of this book is uncertain forecasting using time series and neural networks based on uncertain observed data. ‘Uncertain’ data - plies information exhibiting inaccuracy, uncertainty and questionability. The uncertainty of individual observations is modeled in this book by fuzziness. Sequences of uncertain observations hence constitute fuzzy time series. By means of new discretization techniques for uncertain data it is now possible to correctly and completely retain data uncertainty in forecasting work. The book presents numerical methods which permit successful forecasting not only in engineering but also in many other ?elds such as environmental science or economics, assuming of course that a suitable sequence of observed data | | 出版日期 | Book 2007 | | 關(guān)鍵詞 | Forecasting; Fuzzy Data; Fuzzy artificial neutral networks; Measure; Random Values; Time series; Uncertain | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-540-37176-2 | | isbn_softcover | 978-3-642-07205-5 | | isbn_ebook | 978-3-540-37176-2 | | copyright | Springer-Verlag Berlin Heidelberg 2007 |
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