Applied time series analysis and innovative computing / Sio-Iong Ao.

Includes bibliographical references.

1. Introduction -- 1. Applied Time Series Analysis -- 1.2. Advances in Innovative Computing Paradigms -- 1.3. Real-World Applications: Innovative Computing Paradigms for Time Series Problems -- 2. Applied Time Series Analysis -- 2.1. Basic Characteristics of Time Series -- 2.2. Autoregression and ARIMA Models -- 2.3. Mathematical Models in the Frequency Domain -- 3. Advances in Innovative Computing Paradigms -- 3.1. Research Advances in Computing Algorithms and Databases -- 3.2. Research Advances in Integration of Hardware, Systems and Networks -- 3.3. Research Advances in Internet, Web and Grid Computing -- 3.4. Research Advances in Visualization, Design and Communication -- 3.5. Advances and Applications for Time Series Problems -- 3.6. An Illustrative Example of Building an Innovative Computing Algorithm for Simulated Time Series -- 4. Real-Word Application I: Developing Innovative Computing Algorithms for Business Time Series -- 4.1. Business Time Series -- 4.2. Advances in Business Forecasting -- 4.3. Developing a Hybrid Intelligent Econometrics Model for Business Forecasting -- 4.4. Application for Tourism Demand Forecasting -- 4.5. Application for Cross-Market Financial Forecasting -- 4.6. Discussions and Further Works -- 5. Real-Word Application II: Developing Innovative Computing Algorithms for Biological Time Series -- 5.1. Biological Time Series -- 5.2. Advances in Experimental Designs for Microarray Time Series -- 5.3. Reverse Engineering of Biological Networks -- 5.4. Models for Biological Network Inference -- 5.5. Discussions and Further Works -- 6. Real-Word Application III: Developing Innovative Computing Algorithms for Astronomical Time Series -- 6.1. Astronomical Time Series -- 6.2. Advances and Applications of Innovative Computing Paradigms -- 6.3. Motivations for Investigating the Quasar Time Series with Innovative Approaches -- 6.4. Advances in Emerging Methods for Quasar Studies -- 6.5. Autocorrelations Analysis of Quasars and Clustering Approach -- 6.6. Discussions and Further Works.