Detail publikace

The Method for Material Corrosion Modelling and Feature Selection with SVM-RFE

Originální název

The Method for Material Corrosion Modelling and Feature Selection with SVM-RFE

Anglický název

The Method for Material Corrosion Modelling and Feature Selection with SVM-RFE

Jazyk

en

Originální abstrakt

Material corrosion has caused more and more losses and costs these years, so the world begins to pay much attention to this problem. In this paper, we mainly discuss the modelling 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 modelling method, a special modelling framework is built. According to the experiments, the priority of this method is established not only on algorithm efficiency but also on predicting precision.

Anglický abstrakt

Material corrosion has caused more and more losses and costs these years, so the world begins to pay much attention to this problem. In this paper, we mainly discuss the modelling 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 modelling method, a special modelling framework is built. According to the experiments, the priority of this method is established not only on algorithm efficiency but also on predicting precision.

BibTex


@inproceedings{BUT75215,
  author="Radim {Burget} and Kamil {Říha} and Dongmei {Fu} and Zhenduo {Fu} and Xintao {Qui}",
  title="The Method for Material Corrosion Modelling and Feature Selection with SVM-RFE",
  annote="Material corrosion has caused more and more losses and costs these years, so the world begins to pay much attention to this problem. In this paper, we mainly discuss the modelling 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 modelling method, a special modelling framework is built. According to the experiments, the priority of this method is established not only on algorithm efficiency but also on predicting precision.",
  booktitle="34th International Conference on Telecommunications and Signal Processing (TSP 2011)",
  chapter="75215",
  howpublished="online",
  year="2011",
  month="august",
  pages="443--447",
  type="conference paper"
}