基于改进粒子群算法的知识主动推送模型

摘要

为解决机械产品智能制造过程中知识的主动推送问题,实现智能化制造中知识资源的优化配置,提出了一种基于改进粒子群算法的知识推送模型.首先以机械产品为对象,构建知识推送模型框架,阐述各个子模块的具体特征信息和功能;其次,对推送过程中的概念知识进行重新定义,并加入到新的知识网络模型中;最后提出了改进粒子群算法,对知识推送匹配过程实施优化.并以底座类零件产品为例进行验证,结果表明该方法有效的提高了检索能力,具有较好的推送效果.%In order to solve the problem of active knowledge pushing in the intelligent manufacturing process of mechanical products, a knowledge push model based on Improved Particle Swarm Optimization ( PSO) is proposed to realize the optimal allocation of knowledge resources in intelligent manufacturing. Firstly, to take mechanical products as the object, to construct knowledge push framework model and state the specific characteristics and information of each model. Secondly, the conceptual knowledge in the push process is defined and added to the new network model. The improved particle swarm algorithm is proposed finally, to optimize the knowledge matching process,. the base parts were taken as examples to vertify the method. The result shows that this method improves the retrieval ability and pushing effect.