摘要
为了快速判别矿井突水水源,进而为防治矿井水害服务,以水质指标为判别因子,应用可拓识别方法,建立了谢桥矿井突水水源判别模型,改进了该方法中经典域的形式,提出以各指标的统计值F来量化各指标的识别能力,并作为确定权重的依据.将结果与模糊综合法、灰色关联度法、Bayes逐步判别分析法分别进行比较,其正确率略高于前两者,与Bayes逐步分析法判别结果相同.
In order to discriminate mine water-bursting source quickly, which is the base of the water-bursting control, the extension identification method was applied to the modeling of water-bursting source discrimination in Xieqiao mine using the indices of water quality as discrimination factor. In the model, the sutra field manifestation was improved by integrating the data field and centralized tendency; and a new weighting method basing on the index discrimination ability quantified by the statistics index F of the concerning indices was proposed. Comparing with Fuzzy Comprehensive method, Degree of Grey Incidence method, and Bayes Stepwise Discrimination method, it has a little higher accuracy than the former two methods and the same as the third.
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2009年第1期33-38,共6页
Journal of China Coal Society
基金
国家自然科学基金资助项目(40672154
40202027)
新世纪优秀人才支持项目(NCET-06-0541)
关键词
可拓识别
矿井突水
水源判别
物元
权重
extension identification
mine water-bursting
water-bursting source discrimination
matter element
weight
