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机构地区:[1]江苏师范大学测绘学院,江苏徐州221116 [2]中国矿业大学国土环境与灾害监测国家测绘局重点实验室,江苏徐州221116
出 处:《煤矿开采》2013年第5期17-20,共4页Coal Mining Technology
基 金:国家自然科学基金项目(41272389;40772191);徐州师范大学博士学位教师科研支持项目(11XLR02);国土环境与灾害监测国家测绘局重点实验室开放基金资助项目(LEDM2011B10)
摘 要:针对采动区建筑物损害影响因素的多样性、模糊性、权重不均衡性等特点,提出了建筑物采动损害的熵权模糊识别模型。在分析建筑物采动损害影响因素的基础上,收集学习样本数据,通过建立单因素隶属函数确定隶属度,并采用熵权法确定各影响因素的权重,根据模糊数学理论计算研究对象的模糊综合隶属度,然后按照最大隶属度原则评判建筑物的损害等级。实例分析表明,熵权模糊识别模型评定结果与实际情况一致,该模型综合采动区地质、采矿条件及建筑物状况等多种因素的影响,并顾及了各影响因素之间的不同权重,且算法简单,便于实现,具有较高实用价值。Entropy-weight fuzzy recognition model of buildings influenced by mining was put forward on the basis of diversity, fuzzy and weight unbalance characteristics of buildings damage by mining. Entropy-weight method was applied to determining weights of every in- fluence factor by collecting study example data and setting up single-factor membership function. Fuzzy comprehensive membership of researching object was calculated by fuzzy mathematics theory, and then building damage degree was evaluated by maximum member- ship degree principle. Example analysis showed that evaluation result met with truth. This model comprehensively considered geology, mining condition and building status, and different weights of influence factors. Its arithmetic was simple and liable to realize, so its practical value was high.
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