Fuzzy neural network structure of linguistic dynamic systems based on nonlinear particle swarm optimization

Linguistic dynamic systems (LDS) are dynamic processes involving computing with words instead of numbers for modeling and analysis of complex systems. In this paper, a fuzzy neural network (FNN) structure of LDS base on nonlinear particle swarm optimization was proposed. Finally, experiment results on logistics formulation demonstrated the feasibility and the efficiency of the proposed FNN model.

1. Introduction

During the past few years, linguistic dynamic systems ^[9] have received much attention. Actually, LDS is a methodology of modeling and analysis of complex systems. The goal of studying LDS is to use computing with words ^{[8], [10]} for effective utilization of information at a linguistic level, and for modeling, analysis, control, and evaluation of complex systems.