Shouyang Wang

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Support vector machine (SVM) is a very speci1c type of learning algorithms characterized by the capacity control of the decision function, the use of the kernel functions and the sparsity of the solution. In this paper, we investigate the predictability of 1nancial movement direction with SVM by forecasting the weekly movement direction of NIKKEI 225 index.(More)
In this study, we propose a novel nonlinear ensemble forecasting model integrating generalized linear autoregression (GLAR) with artificial neural networks (ANN) in order to obtain accurate prediction results and ameliorate forecasting performances. We compare the new model’s performance with the two individual forecasting models—GLAR and ANN—as well as(More)
In this study, a multistage neural network ensemble learning model is proposed to evaluate credit risk at the measurement level. The proposed model consists of six stages. In the first stage, a bagging sampling approach is used to generate different training data subsets especially for data shortage. In the second stage, the different neural network models(More)
Due to recent financial crises and regulatory concerns, financial intermediaries’ credit risk assessment is an area of renewed interest in both the academic world and the business community. In this paper, we propose a new fuzzy support vector machine to discriminate good creditors from bad ones. Because in credit scoring areas we usually cannot label one(More)
Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. Artificial neural networks (ANNs) have been widely used as a promising alternative approach for a forecasting task because of several distinguished features. Research efforts on ANNs for(More)
Credit risk analysis is an active research area in financial risk management and credit scoring is one of the key analytical techniques in credit risk evaluation. In this study, a novel intelligent-agent-based fuzzy group decision making (GDM) model is proposed as an effective multicriteria decision analysis (MCDA) tool for credit risk evaluation. In this(More)
Research project selection is an important task for government and private research funding agencies. When a large number of research proposals are received, it is common to group them according to their similarities in research disciplines. The grouped proposals are then assigned to the appropriate experts for peer review. Current methods for grouping(More)
Attribute reduction of an information system is a key problem in rough set theory and its applications. Using computational intelligence (CI) tools to solve such problems has recently fascinated many researchers. In this paper, we consider a meta-heuristic of scatter search to solve the attribute reduction problem in rough set theory. The proposed method,(More)