Prediction of Coal Mine Safety Level Based on LSSVM

Q1 Social Sciences HumanMachine Communication Journal Pub Date : 2010-04-24 DOI:10.1109/MVHI.2010.71
Desheng Liu, Zhiru Xu, Wei Wang, Lei Wang
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引用次数: 2

Abstract

Coal mine disaster has a serious threat to production and safety, mine safety prediction is an extremely challenging problem from many perspectives. This paper describes a generic fusion model for coal mine safety combining information from several physically different sensors aiming to the detection, monitoring and crisis management of such natural hazards. A conduct model base on least squares support vector machine (LSSVM) is proposed. Experimental results from the coal mine sensors are presented
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基于LSSVM的煤矿安全等级预测
煤矿灾害严重威胁着煤矿的生产和安全,煤矿安全预测是一个从多方面都极具挑战性的问题。针对煤矿自然灾害的探测、监测和危机管理问题,提出了一种综合多种物理传感器信息的煤矿安全通用融合模型。提出了一种基于最小二乘支持向量机(LSSVM)的行为模型。给出了矿井传感器的实验结果
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来源期刊
CiteScore
10.00
自引率
0.00%
发文量
10
审稿时长
8 weeks
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