Sep 20, 2019 · By comparing the prediction results of BP neural network and SVM model, it is found that the FA-SVM model has the highest prediction accuracy, ...
FA-SVM model to predict the coal and gas outburst grade of specific coal mines. 2 Algorithm principle. 2.1 Factor analysis. Fctor Analysis (FA) is a method ...
The results show that: Principal component analysis improves the prediction efficiency and accuracy of FA-SVM model. The accuracy rate of PCA-FA-SVM model ...
Bibliographic details on Prediction of coal and gas outburst grade based on factor analysis and SVM model.
This paper presents a development method for coal and gas outburst area forecast on the basis of the SVM technique. Firstly, the character space is divided into ...
The results show that based on the training sets and test set in this study, the prediction accuracy of SVM is higher than that of Back Propagation Neural ...
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Prediction of coal and gas outburst grade based on factor analysis and SVM model[C]//Proceedings of the 2019 International Conference on Robotics ...
A multi-class SVM classifier is applied to predict the coal and gas outburst in the paper. In this model, the dominant factors are the input vectors and the ...
Missing: grade | Show results with:grade
TL;DR: Through simulation test, it is proved that SVM can work efficiently on the coal and gas outburst prediction and the arithmetic Support Vector Machine is ...
Mar 22, 2020 · The present research uses grey relational analysis (GRA) to analyse and investigate the key factors of outburst events. It is characterized by ...
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