基于粒子群算法的模糊插值建模方法研究

摘要

Considering the limitations of conventional fuzzy inference adopting a single membership function, here we propose a kind of Gauss-type membership function of adjustable parameters and create a kind of fuzzy inference model of nonlinear systems based on adjustable parameters, and use particle swarm algorithm to optimize system parameters, the simulation results show the effectiveness of the proposed method.%由于传统模糊建模方法中模型参数都是人们根据经验选取的,它对于不同系统的动态跟踪能力不同,泛化能力差.针对常规模糊推理的局限性,本文提出一种基于参数的模糊插值建模方法.设计了模糊糊理系统的模型和参数调整方案,利用粒子群算法优化模型中的参数,仿真结果表明该方法的有效性.