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首页> 外文期刊>Journal of Computers >The new Development in Support Vector Machine Algorithm Theory and Its Application
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The new Development in Support Vector Machine Algorithm Theory and Its Application

机译:支持向量机算法理论的新发展及其应用

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摘要

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.
机译:针对分类问题,提出了组合优化的最小二乘支持向量机算法(COLS-SVM)。在对COLS-SVM进行算法分析和改进的基础上,改进后的COLS-SVM可用于个人信用评估。对于回归问题,基于对支持向量回归算法的分析,选择了合适的核函数和参数。提出了基于SVR算法的煤矿地下水位预测模型,并对模型进行了改进。在另一个回归问题中,它改进了支持向量回归(SORR)算法的连续过松弛,以测量涉及医学中三种血浆脂蛋白(VLDL,LDL,HDL)的血液样本中的胆固醇含量。数值实验结果表明,改进的COLS-SVM算法,矿井地下水位预测改进模型和改进的SORR算法是有效的。

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