Prediction of coal and gas outburst based on support vector machine

Yabing Ma

doi:10.1117/12.2660297

22 November 2022 Prediction of coal and gas outburst based on support vector machine

Yabing Ma

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124750N (2022) https://doi.org/10.1117/12.2660297
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

Coal and gas disasters occur frequently, which not only cause casualties, but also bring economic losses. The prediction of coal and gas outburst has important research significance. In this paper, a security combination prediction model for building projects based on PCA-PSO-SVM is proposed. Principal component analysis was used for dimension reduction to remove the principal component with low contribution rate, PSO was used to avoid the blindness of selecting parameters of SVM manually. The average prediction accuracy of this model is 93.85%. Compared with the traditional method, the prediction accuracy and the calculation speed is faster.

Citation Download Citation

Yabing Ma "Prediction of coal and gas outburst based on support vector machine", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124750N (22 November 2022); https://doi.org/10.1117/12.2660297

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