Overview
- Updates the reader on the latest advances in time series analysis and forecasting
- Highlights a variety of real-world applications in energy forecasting, computational intelligence and forecasting big data problems
- Brings together experts from various disciplines, ranging from statistics to econometrics and computer science
Part of the book series: Contributions to Statistics (CONTRIB.STAT.)
Included in the following conference series:
Conference proceedings info: ITISE 2019.
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About this book
This book presents a selection of peer-reviewed contributions on the latest advances in time series analysis, presented at the International Conference on Time Series and Forecasting (ITISE 2019), held in Granada, Spain, on September 25-27, 2019. The first two parts of the book present theoretical contributions on statistical and advanced mathematical methods, and on econometric models, financial forecasting and risk analysis. The remaining four parts include practical contributions on time series analysis in energy; complex/big data time series and forecasting; time series analysis with computational intelligence; and time series analysis and prediction for other real-world problems. Given this mix of topics, readers will acquire a more comprehensive perspective on the field of time series analysis and forecasting.
The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.
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Keywords
- time series analysis
- forecasting theory and adjustment
- econometric models and forecasting
- complex and big data time series
- hierarchical forecasting
- energy forecasting
- financial forecasting
- times series in energy
- time series with computational intelligence
- prediction of time series
- artificial intelligence
- pattern recognition
- statistical methods for time series
- risk analysis
- mathematical finance
Table of contents (29 papers)
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Front Matter
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Advanced Statistical and Mathematical Methods for Time Series Analysis
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Front Matter
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Econometric Models and Forecasting
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Front Matter
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Energy Time Series Forecasting
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Front Matter
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Forecasting Complex/Big Data Problems
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Front Matter
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Other volumes
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Theory and Applications of Time Series Analysis
Editors and Affiliations
About the editors
Olga Valenzuela is an Associate Professor at the Department of Applied Mathematics, University of Granada, Spain, where she received her Ph.D. in 2003. She has worked as an invited researcher at the Department of Statistics, University of Jaen, Spain, and at the Department of Computer and Information Science, University of Genova, Italy. Her research interests include optimization theory and applications, statistical analysis, fuzzy systems, neural networks, time series forecasting using linear and non-linear methods, evolutionary computation and bioinformatics. She has published more than 65 papers listed in the Web of Science.
Fernando Rojas is an Associate Professor at the University of Granada, Spain, where he received his Ph.D. in 2004. His research focuses on signal processing, artificial intelligence techniques for optimization, including evolutionary computation, fuzzy logic, neural networks etc., and the study of computer architectures for parallel processing in complex problems, such as time series prediction. He has published over 25 articles in JCR-indexed journals. A former coordinator of the Master’s Degree in Computer and Network Engineering at the University of Granada, he has been the secretary of the Master’s Degree in Data Science and Computer Engineering since 2014, and the secretary of the Department of Architecture and Computer Technology at the University of Granada since 2018.
Luis Javier Herrera is an Associate Professor at the University of Granada, Spain, where he received his Ph.D. in 2006. His research focuses on machine learning techniques (fuzzy logic, deep learning, genetic algorithms, etc.), and on their optimization and application over a wide range of scientific problems related to classification, approximation and time series prediction, sometimes requiring high-performance computing systems. These applications include relevant problems in several fields such as biomedicine, bioinformatics, biochemistry, physics, optics, etc. He has published more than 40 papers in JCR-indexed journals. Over the last several years, he has (co-)led a number of research projects backed by national and regional funding entities.
Héctor Pomares has been a Full Professor at the University of Granada, Spain, since 2001. He has published more than 50 articles in JCR-indexed journals and contributed over 150 papers to international conferences. He has led or participated in 15 national projects, one independent R&D Excellence project and 13 contracts for innovative research through the University of Granada Foundation Company and the Office of Transfer of Research Results. He has been a visiting researcher at numerous prestigious research centers outside Spain. He is currently a member of the editorial board of the Journal of Applied Mathematics (JCR-indexed) and the coordinator of the Master’s Degree in Computer & Network Engineering at the University of Granada.
Ignacio Rojas is a Full Professor at the Department of Computer Architecture and Computer Technology, University of Granada, Spain. Throughout his research career, he has served as a principal investigator or otherwise participated in more than 20 research projects obtained in competitive tenders, including projects for the European Union, the I+D+I Spanish National Government and the Unit of Excellence of the Ministry of Innovation, Science and Enterprise Junta de Andalucía. He has published more than 260 scientific contributions listed in the Web of Science, including 90 articles in JCR-indexed journals.
Bibliographic Information
Book Title: Theory and Applications of Time Series Analysis
Book Subtitle: Selected Contributions from ITISE 2019
Editors: Olga Valenzuela, Fernando Rojas, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas
Series Title: Contributions to Statistics
DOI: https://doi.org/10.1007/978-3-030-56219-9
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-56218-2Published: 21 November 2020
Softcover ISBN: 978-3-030-56221-2Published: 21 November 2021
eBook ISBN: 978-3-030-56219-9Published: 20 November 2020
Series ISSN: 1431-1968
Series E-ISSN: 2628-8966
Edition Number: 1
Number of Pages: XIV, 460
Number of Illustrations: 54 b/w illustrations, 141 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Economic Theory/Quantitative Economics/Mathematical Methods, Probability and Statistics in Computer Science, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Applications of Mathematics, Artificial Intelligence