Support vector regression applied to materials optimization of sialon ceramics

@inproceedings{Xu2006SupportVR,
  title={Support vector regression applied to materials optimization of sialon ceramics},
  author={Liu Xu and Lu Wencong and Jin Shengli and Li Yawei and Chen Nian-yi},
  year={2006}
}
Partial Least Squares (PLS) and Back Propagation Artificial Neural Network (BP-ANN) are widely known machine learning techniques for materials optimization, whereas Support Vector Machine (SVM) is seldom used in materials science. In this paper, Support Vector Regression (SVR), a machine learning technology based on statistical learning theory (SLT), was applied to predict the cold modulus of sialon ceramic with satisfactory results. In a benchmark test, the performances of SVR were compared… CONTINUE READING

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