基于改进演化算法的空间数据聚类在重大危险源动态分级中的应用

Application of Spatial Data Clustering in Dynamic Classification of Major Hazards Based on Improved Evolutionary Algorithm

将改进演化算法的空间数据聚类法应用到重大危险源动态分级中,并增加计算各个聚类质心到绝对安全样本距离这一步骤,实现了对重大危险源的动态分级。40例重大危险源分级验证表明,基于改进演化算法的空间数据聚类重大危险源动态分级法是可行的,有利于从严控制重大危险源。

A spatial data clustering method based on improved evolutionary algorithm was applied to the dynamic classification of major hazards. By adding the step, that calculating the distance between centroid of each cluster with the absolute safety sample, the dynamic classification of major hazards was realized. Verification by 40 examples of major hazards classification proved that the new method was feasible and conducive to strictly control major hazards.