摘要
受风险指标影响,现有方法电网路径匹配效果不佳,无法获得成本最佳路线,因此,设计基于多维信息特征映射的电网风险区段路径匹配模型。采集电网风险区段路径数据并对其进行预处理,采用SNM方法对数据实施二次排序与清洗。通过3D mine软件,根据路径数据与地理特征信息构建电网风险区段路径的地理模型,提取电网风险区段路径特征。根据获取的特征结果,建立多维信息特征映射模型,得出多维信息特征相斥度函数,并采用BPSO算法优化与映射函数相应的权重值,实现电网风险区段路径匹配。分析实验结果可知,所设计模型能够有效躲避风险障碍,能够得出最佳成本路线。
Due to the impact of risk indicators,the existing methods of power grid path matching are not effective and can not get the best cost route.Therefore,a multidimensional information feature mapping based power grid section path matching model is designed.Collect and preprocess the path data of power grid risk section,and the SNM method is used to sort and clean the data.Through 3D mine software,according to the path data and geographic feature information,the geographic model of power grid risk section path is constructed,and the characteristics of power grid risk section path are extracted.According to the feature results,the multidimensional information feature mapping model is established,the multidimensional information feature exclusion function is obtained,and BPSO algorithm is used to optimize the weight value corresponding to the mapping function,so as to realize the path matching of power grid risk section.Analysis of the experimental results shows that the designed model can effectively avoid the risk obstacles and get the best cost path.
作者
刘世涛
杨凯
伍弘
何宁辉
LIU Shitao;YANG Kai;WU Hong;HE Ninghui(Power Research Institute of State Grid Ningxia Electric Power Co.,Ltd.,Yinchuan 750011,China)
出处
《高压电器》
CAS
CSCD
北大核心
2020年第9期87-93,共7页
High Voltage Apparatus
基金
宁夏自然科学基金资助项目(基于大数据挖掘的电网设备运维检修技术研究与应用)。