What is it about?

Coal mine revelation data is constructed as a dataset, and two data pre-processing methods, PCA and SOM, and three SVM parameter search methods, GA, PSO and GWO, are used for experimental comparison. The combined model is used for mine fault identification, and the SOM-GWO-SVM achieves optimal fault interpretation accuracy.

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Why is it important?



Machine learning is a new idea for intelligent development of coal mine structural exploration

Yufei 宫

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This page is a summary of: Seismic fault identification in coal mines based on the self-organizing map-gray wolf optimizer-support vector machine algorithm, Interpretation, January 2024, Society of Exploration Geophysicists,
DOI: 10.1190/int-2023-0025.1.
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