基于SVM-RFE的材料腐蚀建模与特征选择方法

Xintao Qiu, Dongmei Fu, Zhenduo Fu, K. Říha, Radim Burget
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引用次数: 6

摘要

近年来,材料腐蚀造成的损失和成本越来越大,引起了世界各国的广泛关注。本文主要讨论了材料腐蚀数据的建模和特征选择。利用极小样本量的实验数据,建立了腐蚀速率模型。经过专门的数据预处理。将RFE与SVM相结合,提出了一种新的特征选择方法SVM-RFE。然后将该特征选择方法与支持向量机建模方法相结合,构建了一个特殊的建模框架。实验结果表明,该方法的优先级不仅体现在算法效率上,还体现在预测精度上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The method for material corrosion modelling and feature selection with SVM-RFE
Material corrosion has caused more and more losses and costs these years, so the world begin to pay much attention to this problem. In this paper, we mainly discuss the modeling and feature selection of Material corrosion data. With our experimental data with very small sample size, a model of corrosion rate is built. After specialized data preprocessing. By combining RFE and SVM, a novel feature selection method SVM-RFE is introduced. Then integrating this feature selection method and SVM modeling method, a special modeling framework is built. According to the experiments, the priority of this method is established not only on algorithm efficiency but also on predicting precision.
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