Multiscale forecasting models. (2018)

• Record Type: Book
• Further Information: Note: Lida Mercedes Barba Maggi.
• Authors: Maggi, Lida Mercedes Barba
• Contents: Intro; Preface; Acknowledgments; Contents; List of Figures; List of Tables; Acronyms; 1 Times Series Analysis; 1.1 Time Series; 1.2 Analysis Tools; 1.3 Linear Autoregressive Models; 1.4 Artificial Neural Networks; 1.5 Forecasting Accuracy Measures; 1.6 Empirical Application: Traffic Accidents Forecasting; 1.6.1 Smoothing Data via Moving Average; 1.6.2 One-Step Ahead Forecasting Based on AR Model; 1.6.3 One-Step Ahead Forecasting Based on ANN-RPROP; 1.6.4 One-Step Ahead Forecasting Based on ANN-LM; 1.7 Chapter Conclusions; References; 2 Forecasting Based on Hankel Singular Value Decomposition 2.1 Singular Value Decomposition2.1.1 Eigenvalues and Eigenvectors; 2.1.2 Matrix Diagonalization; 2.1.3 SVD Theorem; 2.2 Hankel Singular Value Decomposition; 2.2.1 Embedding; 2.2.2 Decomposition; 2.2.3 Unembedding; 2.2.4 Window Length Selection; 2.3 Forecasting Based on HSVD; 2.3.1 ARIMA Forecasting Based on HSVD; 2.3.2 ANN Forecasting Based on HSVD; 2.4 Empirical Application: Hankel Singular Value Decomposition for Traffic Accidents Forecasting; 2.4.1 Background; 2.4.2 Data Description; 2.4.3 Data Preprocessing Based on HSVD; 2.4.4 Forecasting Models; 2.4.5 HSVD-ARIMA; 2.4.6 HSVD-ANN 2.4.7 Pitman's Correlation Test2.5 Chapter Conclusions; References; 3 Multi-Step Ahead Forecasting; 3.1 Background; 3.2 Strategies for Multi-Step Ahead Forecasting; 3.2.1 Iterative Strategy; 3.2.2 Direct Forecasting Strategy; 3.2.3 MIMO Forecasting Strategy; 3.3 Singular Spectrum Analysis; 3.3.1 Embedding; 3.3.2 Decomposition; 3.3.3 Grouping; 3.3.4 Diagonal Averaging; 3.4 Windows Length Selection; 3.5 Forecasting Based on Components of Low and High Frequency; 3.5.1 Components Extraction Based on HSVD and SSA; 3.5.2 Multi-Step Ahead Forecasting via AR Model 3.5.3 Multi-Step Ahead Forecasting via ANN3.6 Empirical Application: Multi-Step Ahead Forecasting of Traffic Accidents Based on HSVD and SSA via Direct Strategy; 3.6.1 Background; 3.6.2 Models in Evaluation; 3.6.3 Data Description; 3.6.4 Forecasting; 3.6.4.1 Components Extraction; 3.6.4.2 Prediction Results; 3.7 Empirical Application: Multi-Step Ahead Forecasting of Anchovy and Sardine Fisheries Based on HSVD and SSA via MIMO Strategy; 3.7.1 Background; 3.7.2 Models in Evaluation; 3.7.3 Data Description; 3.7.4 Forecasting; 3.7.4.1 Decomposition in Intrinsic Components 3.7.4.2 Prediction Based on Intrinsic Components3.8 Chapter Conclusions; References; 4 Multilevel Singular Value Decomposition; 4.1 Forecasting Methodology; 4.1.1 Multilevel Singular Value Decomposition; 4.1.2 Multi-Step Ahead Forecasting; 4.2 Wavelet Theory; 4.2.1 Stationary Wavelet Transform; 4.3 Empirical Application: MSVD and SWT for Multi-Step Ahead Traffic Accidents Forecasting; 4.3.1 Background; 4.3.2 Data Description; 4.3.2.1 Decomposition Based on MSVD and SWT; 4.3.2.2 Prediction Through MSVD-MIMO and SWT-MIMO
• Publisher Details: Cham : Springer
• Publication Date: 2018
• Extent: 1 online resource
• Subjects: 519.55; Computer science; Time-series analysis; Forecasting -- Mathematical models; MATHEMATICS / Applied; MATHEMATICS / Probability & Statistics / General; Computers -- Mathematical & Statistical Software; Mathematics -- Algebra -- General; Maths for computer scientists; Algebra; Artificial intelligence; Algebra; Computers -- Intelligence (AI) & Semantics; Artificial intelligence; Electronic books
• Languages: English
• ISBNs: 9783319949925; 3319949926
• Related ISBNs: 9783319949918; 3319949918
• Notes: Note: Online resource; title from PDF title page (EBSCO, viewed August 29, 2018)
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.