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  • Conference proceedings
  • © 2018

Time Series Analysis and Forecasting

Selected Contributions from ITISE 2017

  • 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)

  1. Front Matter

    Pages i-xiii
  2. Advanced Mathematical Methodologies in Time Series

    1. Front Matter

      Pages 1-1
    2. A New Estimation Technique for AR(1) Model with Long-Tailed Symmetric Innovations

      • Ayşen Dener Akkaya, Özlem Türker Bayrak
      Pages 39-63
    3. Prediction of High-Dimensional Time Series with Exogenous Variables Using Generalized Koopman Operator Framework in Reproducing Kernel Hilbert Space

      • Jia-Chen Hua, Farzad Noorian, Philip H. W. Leong, Gemunu Gunaratne, Jorge Gonçalves
      Pages 65-77
  3. Computational Intelligence Methods for Time Series

    1. Front Matter

      Pages 93-93
    2. Deep Learning for Detection of BGP Anomalies

      • Marijana Cosovic, Slobodan Obradovic, Emina Junuz
      Pages 95-113
  4. Dimensionality Reduction and Similarity Measures in Time Series

    1. Front Matter

      Pages 129-129
    2. Linear Trend Filtering via Adaptive LASSO

      • Matúš Maciak
      Pages 131-145
    3. An Efficient Anomaly Detection in Quasi-Periodic Time Series Data—A Case Study with ECG

      • Goutam Chakraborty, Takuya Kamiyama, Hideyuki Takahashi, Tetsuo Kinoshita
      Pages 147-157
    4. Similarity Analysis of Time Interval Data Sets—A Graph Theory Approach

      • Marc Haßler, Christian Kohlschein, Tobias Meisen
      Pages 159-171
  5. Econometric Models

    1. Front Matter

      Pages 185-185
    2. Copulas for Modeling the Relationship Between Inflation and the Exchange Rate

      • Laila Ait Hassou, Fadoua Badaoui, Okou Guei Cyrille, Amine Amar, Abdelhak Zoglat, Elhadj Ezzahid
      Pages 217-228

Other Volumes

  1. Time Series Analysis and Forecasting

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.



Editors and Affiliations

  • ETSIIT, University of Granada, Granada, Spain

    Ignacio Rojas

  • CITIC-UGR and ETSIIT, University of Granada, Granada, Spain

    Héctor Pomares

  • 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

Buy it now

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access