Advances in Time Series Forecasting: Volume 2

Cagdas Hakan Aladag

• Publisher: Bentham Science Publishers
• Year: 2017
• Print ISBN:
  9781681085296
• eBook ISBN:
  9781681085289
• Topic: Mathematics
• Subtopic: Probability & Statistics
• Index: Mathematics

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.

Table of contents

• Welcome
• Table Of Content
• Title
• BENTHAM SCIENCE PUBLISHERS LTD.
• PREFACE
• List of Contributors
• Fuzzy Time Series Forecasting Models Evaluation Based on A Novel Distance Measure
• A New Fuzzy Time Series Forecasting Model with Neural Network Structure
• Two Factors High Order Non Singleton Type-1 and Interval Type-2 Fuzzy Systems for Forecasting Time Series with Genetic Algorithm
• A New Neural Network Model with Deterministic Trend and Seasonality Components for Time Series Forecasting
• A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process
• Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix
• A New High Order Multivariate Fuzzy Time Series Forecasting Model
• Fuzzy Functions Approach for Time Series Forecasting
• Recurrent ANFIS for Time Series Forecasting
• A Hybrid Method for Forecasting of Fuzzy Time Series