TY  - CHAP
AU  - Takashi Kuremoto
AU  - Takaomi Hirata
AU  - Masanao Obayashi
AU  - Shingo Mabu
AU  - Kunikazu Kobayashi
ED  - Chun-Kit Ngan
Y1  - 2019-04-03
PY  - 2019
T1  - Training Deep Neural Networks with Reinforcement Learning for Time Series Forecasting
N2  - 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.
BT  - Time Series Analysis
SP  - Ch. 3
UR  - https://doi.org/10.5772/intechopen.85457
DO  - 10.5772/intechopen.85457
SN  - 978-1-78984-779-6
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-24
ER  -