Prof. Dr Shu-Heng Chen is a professor in the Department of Economics of the National Chengchi University. He serves as the Director of the AI-ECON Research Center, National Chengchi University. Dr. Chen holds a M.A. degree in mathematics and a Ph. D. in Economics from the University of California at Los Angeles. He has more than 150 publications in international journals, edited volumes and conference proceedings. Prof. Dr. Paul P. Wang, has published extensively in the fields of mathematical systems modeling, fuzzy logic, pattern recognition,intelligent ystems,managements of economical systems, and the computational biology and bioinformatics. He has been a co-founder of several corporations including Intelligent Machines Inc. He has served as an EiC of the Information Sciences Journal for two decades and he is the managing editor of the New Mathematics & Natural Computing at present. In addition,he is the founder of JCIS, Inc. and Society for Mathematics of Uncertainty in 2006. Prof. Dr. Tzu-Wen Kuo is an assistant professor in Department of Finance and Banking of Aletheia University in Taiwan. She is also a fellow of AI-ECON research center. Her research interest is Genetic Programming in Economics and Finance.

• Computational Intelligence in Economics and Finance: Shifting the Research Frontier.- An Overview of Insurance Uses of Fuzzy Logic.- Forecasting Agricultural Commodity Prices using Hybrid Neural Networks.- Nonlinear Principal Component Analysis for Withdrawal from the Employment Time Guarantee Fund.- Estimating Female Labor Force Participation through Statistical and Machine Learning Methods: A Comparison.- An Application of Kohonen’s SOFM to the Management of Benchmarking Policies.- Trading Strategies Based on K-means Clustering and Regression Models.- Comparison of Instance-Based Techniques for Learning to Predict Changes in Stock Prices.- Application of an Instance Based Learning Algorithm for Predicting the Stock Market Index.- Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period.- Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms.- Nonlinear Goal-Directed CPPI Strategy.- Hybrid-Agent Organization Modeling: A Logical-Heuristic Approach.

Prof. Dr Shu-Heng Chen is a professor in the Department of Economics of the National Chengchi University. He serves as the Director of the AI-ECON Research Center, National Chengchi University. Dr. Chen holds a M.A. degree in mathematics and a Ph. D. in Economics from the University of California at Los Angeles. He has more than 150 publications in international journals, edited volumes and conference proceedings. Prof. Dr. Paul P. Wang, has published extensively in the fields of mathematical systems modeling, fuzzy logic, pattern recognition,intelligent ystems,managements of economical systems, and the computational biology and bioinformatics. He has been a co-founder of several corporations including Intelligent Machines Inc. He has served as an EiC of the Information Sciences Journal for two decades and he is the managing editor of the New Mathematics & Natural Computing at present. In addition,he is the founder of JCIS, Inc. and Society for Mathematics of Uncertainty in 2006. Prof. Dr. Tzu-Wen Kuo is an assistant professor in Department of Finance and Banking of Aletheia University in Taiwan. She is also a fellow of AI-ECON research center. Her research interest is Genetic Programming in Economics and Finance.

• Computational Intelligence in Economics and Finance: Shifting the Research Frontier.- An Overview of Insurance Uses of Fuzzy Logic.- Forecasting Agricultural Commodity Prices using Hybrid Neural Networks.- Nonlinear Principal Component Analysis for Withdrawal from the Employment Time Guarantee Fund.- Estimating Female Labor Force Participation through Statistical and Machine Learning Methods: A Comparison.- An Application of Kohonen’s SOFM to the Management of Benchmarking Policies.- Trading Strategies Based on K-means Clustering and Regression Models.- Comparison of Instance-Based Techniques for Learning to Predict Changes in Stock Prices.- Application of an Instance Based Learning Algorithm for Predicting the Stock Market Index.- Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period.- Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms.- Nonlinear Goal-Directed CPPI Strategy.- Hybrid-Agent Organization Modeling: A Logical-Heuristic Approach.

Prof. Dr Shu-Heng Chen is a professor in the Department of Economics of the National Chengchi University. He serves as the Director of the AI-ECON Research Center, National Chengchi University. Dr. Chen holds a M.A. degree in mathematics and a Ph. D. in Economics from the University of California at Los Angeles. He has more than 150 publications in international journals, edited volumes and conference proceedings. Prof. Dr. Paul P. Wang, has published extensively in the fields of mathematical systems modeling, fuzzy logic, pattern recognition,intelligent ystems,managements of economical systems, and the computational biology and bioinformatics. He has been a co-founder of several corporations including Intelligent Machines Inc. He has served as an EiC of the Information Sciences Journal for two decades and he is the managing editor of the New Mathematics & Natural Computing at present. In addition,he is the founder of JCIS, Inc. and Society for Mathematics of Uncertainty in 2006. Prof. Dr. Tzu-Wen Kuo is an assistant professor in Department of Finance and Banking of Aletheia University in Taiwan. She is also a fellow of AI-ECON research center. Her research interest is Genetic Programming in Economics and Finance.

• Computational Intelligence in Economics and Finance: Shifting the Research Frontier.- An Overview of Insurance Uses of Fuzzy Logic.- Forecasting Agricultural Commodity Prices using Hybrid Neural Networks.- Nonlinear Principal Component Analysis for Withdrawal from the Employment Time Guarantee Fund.- Estimating Female Labor Force Participation through Statistical and Machine Learning Methods: A Comparison.- An Application of Kohonen’s SOFM to the Management of Benchmarking Policies.- Trading Strategies Based on K-means Clustering and Regression Models.- Comparison of Instance-Based Techniques for Learning to Predict Changes in Stock Prices.- Application of an Instance Based Learning Algorithm for Predicting the Stock Market Index.- Evaluating the Efficiency of Index Fund Selections Over the Fund’s Future Period.- Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms.- Nonlinear Goal-Directed CPPI Strategy.- Hybrid-Agent Organization Modeling: A Logical-Heuristic Approach.