doi: 10.4304/jsw.6.2.273-280
The new Development in Support Vector Machine Algorithm Theory and Its Application
- 1 College of Environment and Spatial Informatics China University of Mining & Technology, Xuzhou, China
- 2 Department of Information and Engineering Shandong University of Science and Technology, Taian, China
- 3 Nanyang Technological University, Singapore, Singapore
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.
Keywords
- COLS-SVM
- SVR
- Individual Credit Evaluat
How to Cite
Liu Taian, Wang Yunjia, Wang Yinlei, and 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. https://doi.org/ 10.4304/jsw.6.2.273-280
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).