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[学科前沿] 【2019新书】Theory and Applications of Time Series Analysis   [推广有奖]

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Theory and Applications of Time Series Analysis: Selected Contributions from ITISE 2018
by Olga Valenzuela (Editor), Fernando Rojas (Editor), Héctor Pomares (Editor), Ignacio Rojas (Editor)

About the Author
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 60 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 26 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.
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 visitor 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 official 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 250 scientific contributions listed in the Web of Science, including 90 articles in JCR-indexed journals.

About this book
This book presents selected peer-reviewed contributions from the International Conference on Time Series and Forecasting, ITISE 2018, held in Granada, Spain, on September 19-21, 2018. The first three parts of the book focus on the theory of time series analysis and forecasting, and discuss statistical methods, modern computational intelligence methodologies, econometric models, financial forecasting, and risk analysis. In turn, the last three parts are dedicated to applied topics and include papers on time series analysis in the earth sciences, energy time series forecasting, and time series analysis and prediction in other real-world problems. The book offers readers valuable insights into the different aspects of time series analysis and forecasting, allowing them to benefit both from its sophisticated and powerful theory, and from its practical applications, which address real-world problems in a range of disciplines.
The ITISE conference series provides a valuable forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.

Brief contents
Advanced Statistical Methods for Time Series Analysis and Forecasting
Identification of Nonstationary Processes Using Noncausal Bidirectional Lattice Filtering 3
Normalized Entropy Aggregation for Inhomogeneous Large-Scale Data 19
Modified Granger Causality in Selected Neighborhoods. 31
Computing Environment for Forecasting Based on System Dynamics Models 43
Novel Order Patterns Recurrence Plot-Based Quantification Measures to Unveil Deterministic Dynamics from Stochastic Processes 57
Time Series Modeling with MATLAB: The SSpace Toolbox 71
Advanced Computational Intelligence Methods for Time Series Analysis and Forecasting
Stacked LSTM Snapshot Ensembles for Time Series Forecasting 87
Change Detection for Streaming Data Using Wavelet-Based Least Squares Density–Difference 99
Selection of Neural Network for Crime Time Series Prediction by Virtual Leave-One-Out Tests. 117
FPGA-Based Echo-State Networks 135
Econometric Models, Financial Forecasting and Risk Analysis
Conditional Heteroskedasticity in Long-Memory Model “FIMACH” for Return Volatilities in Equity Markets 149
Using Subspace Methods to Model Long-Memory Processes 171
Robust Forecasting of Multiple Yield Curves 187
The Changing Shape of Sovereign Default Intensities 203
Permutation Entropy as the Measure of Globalization Process 217
Time Series Analysis in Earth Sciences
Forecasting Subtidal Water Levels and Currents in Estuaries: Assessment of Management Scenarios 229
Spatial Distribution of Climatic Cycles in Andalusia (Southern Spain) 243
Localized Online Weather Predictions with Overnight Adaption 257
Storm Characterization Using a BME Approach 271
Energy Time Series Forecasting
Adaptive Methods for Energy Forecasting of Production and Demand of Solar-Assisted Heating Systems 287
Short-Term Forecast of Wind Turbine Production with Machine Learning Methods: Direct and Indirect Approach 301
Time Series Analysis and Prediction in Other Real Problems
A Simulation of a Custom Inspection in the Airport 319
Comparing Time Series Prediction Approaches for Telecom Analysis 331
Application of Load Forecasting in Thermal Unit Commitment Problems: A Pattern Similarity Approach 347
ICA-Derived Respiration Using an Adaptive R-Peak Detector 363
Author Index 379

Series: Contributions to Statistics
Pages: 380 pages
Publisher: Springer; 1st ed. 2019 edition (October 19, 2019)
Language: English
ISBN-10: 3030260356
ISBN-13: 978-3030260354

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Theory and Applications of Time Series Analysis: Selected Contributions from ITISE 2018
by Olga Val ...
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