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机构地区:[1]中南大学资源与安全工程学院,湖南长沙410083
出 处:《中南大学学报(自然科学版)》2015年第6期2157-2161,共5页Journal of Central South University:Science and Technology
基 金:国家重点基础研究发展计划(973计划)项目(2007CB209402);国家自然科学基金资助项目(面上项目)(51324744)~~
摘 要:将未确知测度理论应用到岩石可爆性分级问题中,提出未确知均值分级方法,建立岩石可爆性分级的未确知均值分级模型;选用岩石容重、岩石抗拉强度、岩石完整性系数作为分级模型的判定指标;以14种岩石的实测判定指标建立分类判别指标的未确知测度函数,并求得各分级样本指标的平均值和单指标测度矩阵;根据信息熵理论确定各指标的权重,利用置信度识别准则对岩石进行判定分级。利用该模型对矿区岩石进行分类预测,并与实测结果进行比较。研究结果表明:利用岩石可爆性分级的未确知均值分级模型所得预测结果与实测结果相吻合,准确率达100%为岩石可爆性分级提供了一条新的途径。The unascertained measurement theory was used to classify the rock mass blastability, and the unascertained average clustering model for classifying blastability of rock mass was established, including three indexes reflecting the blastability of rock mass, i.e., density, tensile strength and intactness coefficient of rock mass. The indexes function of unascertained measure of 14 sets of rock mass samples was established,the indexes were calculated by entropy weight theory, and the prediction for the classification of rock mass blastability was carried out using the rules of credible recognition. Classification of the four rock masses in mining area was predicted using unascertained average clustering model and compared with the actually measured values, and the accurate rate was 100%. The results show that the predicted classification is consistent with the actual measured result, which provides a new way to classify the rock mass blastability.
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