4th International Conference, SCDS 2018, Bangkok, Thailand, August 15-16, 2018, Proceedings /
First Statement of Responsibility
Bee Wah Yap, Azlinah Hj Mohamed, Michael W. Berry (eds.).
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Singapore :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
[2019]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xviii, 404 pages) :
Other Physical Details
illustrations (some color)
SERIES
Series Title
Communications in computer and information science,
Volume Designation
937
ISSN of Series
1865-0929 ;
GENERAL NOTES
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Includes author index.
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International conference proceedings.
CONTENTS NOTE
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Intro; Preface; Organization; Contents; Machine and Deep Learning; A Hybrid Singular Spectrum Analysis and Neural Networks for Forecasting Inflow and Outflow Currency of Bank Indonesia; Abstract; 1 Introduction; 2 Materials and Methods; 2.1 ARIMAX; 2.2 Singular Spectrum Analysis (SSA); 2.3 Neural Networks; 2.4 Hybrid Singular Spectrum Analysis and Neural Network; 2.5 Model Evaluation; 3 Results; 3.1 Simulation Study; 3.2 Inflow and Outflow Data; 3.3 Forecasting Inflow and Outflow Data Using ARIMAX; 3.4 Forecasting Inflow and Outflow Data Using SSA-NN; 4 Conclusion; Acknowledgements
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2.1 Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF)2.2 The ARIMA Model; 2.3 Artificial Neural Network; 2.4 Deep Feedforward Network; 3 Dataset and Methodology; 3.1 Dataset; 3.2 Methodology; 4 PACF Based Deep Neural Network Implementation; 4.1 Preliminary Analysis; 4.2 Feature Selection; 4.3 Optimal Neural Architecture: Hyperparameters Tuning; 4.4 Test Set Prediction; 5 ARIMA Based Deep Neural Network; 5.1 Procedure Implementation; 6 Discussion and Future Works; Acknowledgements; References
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2.1 Vector Autoregressive (VAR) Model2.2 Generalized Space Time Autoregressive (GSTAR) Model; 2.3 Support Vector Regression (SVR); 2.4 Model Selection; 3 Data and Method; 4 Empirical Results; 4.1 Descriptive Statistics; 4.2 VAR Modeling; 4.3 GSTAR Modeling; 4.4 Forecasting Using VAR-SVR and GSTAR-SVR Model; 5 Conclusion; Acknowledgement; References; Feature and Architecture Selection on Deep Feedforward Network for Roll Motion Time Series Prediction; Abstract; 1 Introduction; 2 Time Series Analysis: Concept and Methods
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Simulation Study of Feature Selection on Survival Least Square Support Vector Machines with Application to Health DataAbstract; 1 Introduction; 2 Literature Review; 2.1 Least Square SVM for Survival Analysis; 2.2 Performance Measure; 3 Data Description and Methodology; 3.1 Data Description; 3.2 Methodology; 4 Empirical Results; 4.1 Simulation Study; 4.2 Application on Health Data; 5 Conclusion; Acknowledgement; References; VAR and GSTAR-Based Feature Selection in Support Vector Regression for Multivariate Spatio-Temporal Forecasting; Abstract; 1 Introduction; 2 Literature Review
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SUMMARY OR ABSTRACT
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This book constitutes the refereed proceedings of the 4th International Conference on Soft Computing in Data Science, SCDS 2018, held in Bangkok, Thailand, in August 2018. The 30 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on machine and deep learning, image processing, financial and fuzzy mathematics, optimization algorithms, data and text analytics, data visualization.