- 130 pages
- English
- PDF
- Available on iOS & Android
About This Book
This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This book is divided into three sections and each section includes two chapters. Section 1 discusses analyzing multivariate and fuzzy time series. Section 2 focuses on developing deep neural networks for time series forecasting and classification. Section 3 describes solving real-world domain-specific problems using time series techniques. The concepts and techniques contained in this book cover topics in time series research that will be of interest to students, researchers, practitioners, and professors in time series forecasting and classification, data analytics, machine learning, deep learning, and artificial intelligence.
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Table of contents
- Time Series Analysis - Data, Methods, and Applications
- Contents
- Preface
- Section 1 Mining Complex Patterns inTime Series Data
- Section 2 Deep Neural Networks forTime Series Analytics
- Section 3 Time Series Forecasting in Real-World Problems