Advances in Time Series Analysis and Forecasting (eBook, PDF)

Selected Contributions from ITISE 2016
Redaktion: Rojas, Ignacio; Valenzuela, Olga; Pomares, Héctor

• Format: PDF

Produktbeschreibung

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016.

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 rese

arch encompassing the disciplines of computer science, mathematics, statistics and econometrics.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 414
• Erscheinungstermin: 31. Juli 2017
• Englisch
• ISBN-13: 9783319557892
• Artikelnr.: 53063609

Autorenporträt

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 calls including projects of the European Union, the I+D+I Spanish National Government and projects Excellence of the Ministry of Innovation, Science and Enterprise Junta de Andalucía. He has published more than 210 scientific contributions reflected in the database ISI Web of Knowledge, thereof 87 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 with more than 150 papers in international conferences. He has led or participated in 15 national projects, one autonomic R&D Excellence project and 13 contracts signed for innovativeresearch through the University of Granada Foundation Company and the Office of Transfer of Research Results. He has made 6 stays longer than one month in prestigious research centers outside of Spain, all of them with a competitive nature. 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 current research interests include optimization theory and applications, statistical analysis, fuzzy systems, neural networks, time series forecasting using linear and non-line ar methods,evolutionary computation and bioinformatics. She has made several stays longer than one month in prestigious research centers outside of Spain, all of them with a competitive nature. She has published more than 67 contributions reflected in the database ISI Web of Knowledge.

Inhaltsangabe

Preface.- Part I: Analysis of Irregularly Sampled Time Series: Techniques, Algorithms and Case Studies.- Scientific Contributions.- Part II: Multi-scale Analysis of Univariate and Multivariate Time Series.- Scientific Contributions.- Part III: Linear and Non-linear Time Series Models.- Scientific Contributions.- Part IV: Advanced Time Series Forecasting Methods.- Scientific Contributions.- Part V: Applications in Time Series Analysis and Forecasting.- Scientific Contributions.- Author Index.