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Advances in Time Series Forecasting: Volume 2

by Cagdas Hakan Aladag

Advanced forecasting methods, with a focus on fuzzy time series

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AlbakiReads Editorial

Advanced forecasting methods, with a focus on fuzzy time series

This second volume surveys advanced approaches to time series forecasting, centering on fuzzy time series methods and their applications. Its chapters bring these methods together with topics including neural networks, high-order multivariate systems, deterministic trends, and distance measurement. The emphasis is on forecasting frameworks and how they are applied, giving the book a technical scope within probability and statistics. It offers a subject-focused reference point for exploring how different methods and concepts can be combined in forecasting work.

Good fit for readers who enjoy

  • MSc and PhD students studying time series forecasting
  • Researchers and academic personnel exploring advanced forecasting methods
  • Readers interested in fuzzy time series and hybrid forecasting approaches

Themes

Time series forecastingFuzzy time seriesNeural networksMultivariate systemsForecasting applications

Based on publisher information and book metadata.

Book overview

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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