Advances in Time Series Forecasting: Volume 2

Nonfiction, Science & Nature, Mathematics, Probability, Statistics
Cover of the book Advances in Time Series Forecasting: Volume 2 by Cagdas Hakan Aladag, Bentham Science Publishers
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Author: Cagdas Hakan Aladag ISBN: 9781681085289
Publisher: Bentham Science Publishers Publication: December 5, 2017
Imprint: Language: English
Author: Cagdas Hakan Aladag
ISBN: 9781681085289
Publisher: Bentham Science Publishers
Publication: December 5, 2017
Imprint:
Language: English

This volume is a valuable source of recent knowledge about advanced time series forecasting techniques such as artificial neural networks, fuzzy time series, or hybrid approaches. New forecasting frameworks are discussed and their application is demonstrated. The second volume of the series includes applications of some powerful forecasting approaches with a focus on fuzzy time series methods. Chapters integrate these methods with concepts such as neural networks, high order multivariate systems, deterministic trends, distance measurement and much more. The chapters are contributed by eminent scholars and serve to motivate and accelerate future progress while introducing new branches of time series forecasting. This book is a valuable resource for MSc and PhD students, academic personnel and researchers seeking updated and critically important information on the concepts of advanced time series forecasting and its applications.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This volume is a valuable source of recent knowledge about advanced time series forecasting techniques such as artificial neural networks, fuzzy time series, or hybrid approaches. New forecasting frameworks are discussed and their application is demonstrated. The second volume of the series includes applications of some powerful forecasting approaches with a focus on fuzzy time series methods. Chapters integrate these methods with concepts such as neural networks, high order multivariate systems, deterministic trends, distance measurement and much more. The chapters are contributed by eminent scholars and serve to motivate and accelerate future progress while introducing new branches of time series forecasting. This book is a valuable resource for MSc and PhD students, academic personnel and researchers seeking updated and critically important information on the concepts of advanced time series forecasting and its applications.

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