Study on case-based reasoning expert system about the matching optimization of particle swarm optimization algorithm

For the weak of the traditional expert system reasoning ability and intelligent level, the problem of the matching expression of the traditional expert system in the reasoning ability and case is solved by using the particle swarm method in this paper. The basic principle and mathematical expression of the particle swarm expert system are described in detail in this paper. By building reasonable keyword importance model, we decide which case adaptation is the highest according to the overall matching value. Finally, the combination of the case and the realization of t he particle swarm optimization algorithm are carried out.