基于混沌粒子群优化算法的电力大规模应急物资管控领域本体模型研究
Research on ontology model of power large-scale emergency material man-agement and control based on Chaotic Particle Swarm Optimization Algo-rithm
李云龙 1徐行1
作者信息
- 1. 国网浙江省电力有限公司温州供电公司,浙江温州 325000
- 折叠
摘要
针对评价指标关系丰富性和可解释性低,不能满足管控领域本体建模需求的问题,提出基于混沌粒子群优化算法的电力大规模应急物资管控领域本体模型.采用混沌粒子群优化算法,设计映射实体对集合.通过评价适应度和稀疏度,更新粒子位置并判断是否停止迭代.计算得到最优映射结果,并使用全局DEA评估模型是否符合要求.实验结果表明,综合考虑关系丰富性和可解释性指标,研究模型在整体上表现相对较好.
Abstract
In response to the problem of low richness and interpretability of evaluation index re-lationships,which cannot meet the ontology modeling requirements of the control field,a chaot-ic particle swarm optimization algorithm based ontology model for large-scale emergency mate-rial control in the power industry is proposed.Using chaotic particle swarm optimization algo-rithm,design a set of mapped entity pairs.By evaluating fitness and sparsity,update particle po-sitions and determine whether to stop iteration.Calculate the optimal mapping result and use global DEA to evaluate whether the model meets the requirements.The experimental results in-dicate that,taking into account the richness and interpretability indicators of relationships,the re-search model performs relatively well overall.
关键词
混沌算法/粒子群算法/电力应急物资/物资管控领域/本体模型/本体映射Key words
chaotic algorithm/particle swarm optimization/power emergency materials/material control field/ontology model/ontology mapping引用本文复制引用
出版年
2024
NETL
NSTL
万方数据