¹College of Environment and Spatial Informatics China University of Mining & Technology, Xuzhou, China
²Department of Information and Engineering Shandong University of Science and Technology, Taian, China
³Nanyang Technological University, Singapore, Singapore

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Abstract—As to classification problem, this paper puts forward the combinatorial optimization least squares support vector machine algorithm (COLS-SVM). Based on algorithmic analysis of COLS-SVM and improves on it, the improved COLS-SVM can be used on individual credit evaluation. As to regression problem, appropriate kernel function and parameters were selected based on the analysis of support vector regression (SVR) algorithm. This paper proposes the forecasting model of coal mine ground-waterlevel based on SVR algorithm and improves on it. In another regression problem, it improves on successive overrelaxation for support vector regression (SORR) algorithm to measure the cholesterol content of a blood sample concerning the three kinds of plasma lipoproteins (VLDL, LDL, HDL) in medical science. The numerical experiment results show that the improved COLS-SVM algorithm and Mine Ground-water-level Forecasting improved Model and improved SORR algorithm are effective.

Index Terms—COLS-SVM, SVR, Individual Credit Evaluation, the Forecasting Model of Coal Mine Groundwater- level, Plasma Lipoprotein Cholesterol Measurement

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Cite: Liu Taian, Wang Yunjia, Wang Yinlei, Liu Wentong, "The new Development in Support Vector Machine Algorithm Theory and Its Application," Journal of Software vol. 6, no. 2, pp. 273-280, 2011.