Editors:
- Presents the latest developments in time series analysis and forecasting
- Provides both theoretical findings and real-world applications
- Brings together experts from various disciplines, ranging from statistics to econometrics to computer science
Part of the book series: Contributions to Statistics (CONTRIB.STAT.)
Conference series link(s): ITISE: International Conference on Time Series and Forecasting
Conference proceedings info: ITISE 2017.
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Table of contents (22 papers)
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Front Matter
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Advanced Mathematical Methodologies in Time Series
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Front Matter
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Computational Intelligence Methods for Time Series
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Front Matter
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Dimensionality Reduction and Similarity Measures in Time Series
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Front Matter
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Econometric Models
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Front Matter
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About this book
This book presents selected peer-reviewed contributions from the International Work-Conference on Time Series, ITISE 2017, held in Granada, Spain, September 18-20, 2017. It discusses topics in time series analysis and forecasting, including advanced mathematical methodology, computational intelligence methods for time series, dimensionality reduction and similarity measures, econometric models, energy time series forecasting, forecasting in real problems, online learning in time series as well as high-dimensional and complex/big data time series.
The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.
Keywords
- 62-XX, 68-XX, 60-XX, 58-XX, 37-XX
- Time series
- Forecasting
- Mathematical methodology for time series
- Computational intelligence methods
- Forecasting in real problems
- Energy time series forecasting
- Dimensionality reduction
- Similarity measures
- Econometric models
- High-dimensional data
- Complex data
- Big data
- Artificial intelligence
- Pattern recognition
- On-line learning in time series
Editors and Affiliations
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ETSIIT, University of Granada, Granada, Spain
Ignacio Rojas
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CITIC-UGR and ETSIIT, University of Granada, Granada, Spain
Héctor Pomares
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Faculty of Sciences, University of Granada, Granada, Spain
Olga Valenzuela
About the editors
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 participated in more than 20 research projects obtained in competitive tenders, including projects of 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 250 scientific contributions reflected in Web of Science, including 145 articles in JCR-indexed journals.
Héctor Pomares has been a full professor at the University of Granada in Spain since 2001. He has published more than 50 articles in JCR-indexed journals and contributed over 150 papers at international conferences. He has led or participated in 15 national projects, one autonomic R&D Excellence project and 13 contracts for innovative research through the Universityof Granada Foundation Company and the Office of Transfer of Research Results. He has been a visitor at numerous prestigious research centers outside Spain. He is a member of the editorial board of the Journal of Applied Mathematics (JCR-indexed) and is the coordinator of the Official Master's Degree in Computer & Network Engineering at the University of Granada.
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 was 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 been a visitor at numerous prestigious research centers outside Spain. She has published more than 72 papers reflected in Web of Science.
Bibliographic Information
Book Title: Time Series Analysis and Forecasting
Book Subtitle: Selected Contributions from ITISE 2017
Editors: Ignacio Rojas, Héctor Pomares, Olga Valenzuela
Series Title: Contributions to Statistics
DOI: https://doi.org/10.1007/978-3-319-96944-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Hardcover ISBN: 978-3-319-96943-5Published: 04 October 2018
Softcover ISBN: 978-3-030-07276-6Published: 28 December 2018
eBook ISBN: 978-3-319-96944-2Published: 03 October 2018
Series ISSN: 1431-1968
Series E-ISSN: 2628-8966
Edition Number: 1
Number of Pages: XIII, 340
Number of Illustrations: 42 b/w illustrations, 60 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Econometrics, Probability and Statistics in Computer Science, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Probability Theory and Stochastic Processes