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Time Series Analysis and Forecasting

Selected Contributions from ITISE 2023

  • Conference proceedings
  • Oct 2024
  • Latest edition

Overview

  • Updates the reader on the latest developments in time series analysis and forecasting
  • Covers a broad range of modern topics and applications, including machine learning and energy research
  • Brings together experts from various disciplines, ranging from statistics to econometrics and computer science

Part of the book series: Contributions to Statistics (CONTRIB.STAT.)

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About this book

This volume on the latest developments in the theory and applications of time series analysis and forecasting comprises a selection of refereed papers presented at the 9th International Conference on Time Series and Forecasting, ITISE 2023, held in Gran Canaria, Spain, July 12-14, 2023. It is divided into several parts that address modern theoretical aspects of time series analysis, advanced econometric methods, time series and machine learning, financial forecasting and risk analysis, and applications to various disciplines, including econometrics and energy research. The broad range of topics and applications presented, including matters of particular relevance for sustainable development, gives readers a modern perspective on the subject.

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.

Keywords

  • Time Series Analysis
  • Forecasting
  • Econometric Time Series
  • Energy Time Series
  • Machine Learning
  • Financial Forecasting
  • Risk Analysis
  • Time Series Applications
  • Econometrics

Editors and Affiliations

  • Department of Applied Mathematics, University of Granada, Granada, Spain

    Olga Valenzuela

  • Department of Computer Engineering, Automatics and Robotics, University of Granada, Granada, Spain

    Fernando Rojas, Luis Javier Herrera

  • Department of Computer Architecture and Computer Technology, University of Granada, Granada, Spain

    Héctor Pomares, Ignacio Rojas

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. His research focuses on the study of complex multidimensional systems using intelligent systems, supported by high-performance computing platforms, and their applications in various fields, including bioinformatics, biomedicine, and time series prediction. Throughout his research career, he has served as a principal investigator or otherwise participated in more than 24 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 more than 270 publications listed in the Web of Science, including more than 120 articles in JCR-indexed journals. He has actively participated in more than 125 international conferences, supervised 25 doctoral theses, and organized various international conferences, workshops and special sessions.

Bibliographic Information

  • Book Title: Time Series Analysis and Forecasting

  • Book Subtitle: Selected Contributions from ITISE 2023

  • Editors: Olga Valenzuela, Fernando Rojas, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas

  • Series Title: Contributions to Statistics

  • 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 license to Springer Nature Switzerland AG 2025

  • Hardcover ISBN: 978-3-031-69749-4Due: 06 November 2024

  • Softcover ISBN: 978-3-031-69752-4Due: 06 November 2024

  • eBook ISBN: 978-3-031-69750-0Due: 06 November 2024

  • Series ISSN: 1431-1968

  • Series E-ISSN: 2628-8966

  • Edition Number: 1

  • Number of Pages: X, 330

  • Number of Illustrations: 23 b/w illustrations, 75 illustrations in colour

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