Underground coal gangue recognition based on composite fusion of feature and decision
Xiaoyu Li,
Rui Xia,
Rui Kang
et al.
Abstract:The underground coal gangue separation and in-situ filling can reduce environmental pollution, promote the recycling of resources, and ensure the safe operation of mining. However, the harsh environment and abnormal working conditions are a significant challenge to the separation technology. Therefore, it is essential to develop a coal gangue classification method that is highly accurate, robust, and can handle abnormal working conditions. To address the above problems, this paper innovatively combines spectra… Show more
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