现代制造工程Issue(6)：30-44,15.DOI:10.16731/j.cnki.1671-3133.2025.06.004
基于语义相似度与改进PSO算法的云制造能力需求模型与匹配策略研究
Research on cloud manufacturing capability demand model and matching strategy based on semantic similarity and improved PSO algorithm
摘要
Abstract
Addressing the search matching and service composition issues between manufacturing capabilities and task require-ments in the context of intelligent manufacturing resource service sharing in cloud computing environments,this study presents a cloud manufacturing capability demand model and matching strategy based on semantic similarity and an improved Particle Swarm Optimization(PSO)algorithm is presented.First,building upon the proposed cloud manufacturing capability demand model,the concept of domain ontology tree is introduced to calculate concept similarity,sentence similarity,and numerical similarity,thereby achieving intelligent service search for cloud manufacturing capability demands based on semantic similarity.Subsequently,ad-dressing the issue of service composition for cloud manufacturing capabilities,based on analyzing the Quality of Service(QoS)at-tributes of manufacturing capabilities,a service composition method based on an improved PSO algorithm is proposed using the Analytic Hierarchy Process(AHP)to normalize and sum various attributes.Finally,experimental comparisons demonstrate the superiority of the proposed approach over existing methods,leading to the realization of an intelligent matching prototype system for cloud manufacturing capability demands.关键词
云制造能力/任务需求/搜索匹配/服务组合/语义相似度/改进粒子群优化算法Key words
cloud manufacturing capabilities/task demands/search matching/service composition/semantic similarity/improved Particle Swarm Optimization(PSO)algorithm分类
计算机与自动化引用本文复制引用
李晓波,郭银章..基于语义相似度与改进PSO算法的云制造能力需求模型与匹配策略研究[J].现代制造工程,2025,(6):30-44,15.基金项目
国家自然科学基金资助项目(61876123) （61876123）
山西省中央引导地方科技发展资金项目(YDZJSX20231A044) （YDZJSX20231A044）
