基于模糊模式识别的采动区建筑物损害等级预测

为掌握煤矿采动区建筑物损害程度,采用模糊模式识别方法对采动区建筑物损害等级进行预测。首先对30个已知采动区建筑物损害数据进行预处理,根据研究区域井下开采情况、地质条件及建筑物结构等因素,采用模糊聚类方法生成包含4个标准模型的模型库。然后对8个测试样本与标准模型库进行测试,计算样本数据与各个标准模型的贴近度,根据择近原则判断各样本所对应的标准模型。通过计算,8个测试样本预测结果与实测值完全相同,预测结果准确可靠。研究表明使用模糊模式识别方法预测建筑物损害等级是可行的,研究成果为预测矿山采动区建筑物损害等级提供了一种新的方法。

Damage Grade Forecast of Buildings in Mining Area Based on Fuzzy Pattern Recognition

To master the building damage degree in mining areas,fuzzy pattern recognition method is used to forecast the damage grade.Firstly,30 known datum of building damage in mining areas are preprocessed,then a model base including four standard models is established by fuzzy clustering analysis method,according to the underground mining situation,geological conditions and building structure and so on.Afterwards,eight samples have been tested with the standard model base,the closeness between the sample and each of the standard model is calculated,and then the corresponding standard model of each sample is determined based on the principle of choosing nearest.Calculation result shows that the predicted result of the 8 test samples equal to the measured values,therefore they are accurate and reliable.The study shows that using fuzzy recognition method to predict building damage grade is feasible,and it is a new approach of predicting the damage grade of buildings in mining areas.