Abstract:

Aiming at solving the problems of some traditional cluster methods, an improved cluster method based on bi-swarm particle swarm optimization (PSO) algorithm with exchanging particles strategy was proposed. One swarm dynamically updated its inertia weight by a new nonlinear updating formula, and the other employed a constant inertia weight. The two swarms exchanged some particles after each iteration. The method was applied to the cluster of fabric deformation comfort and took the cluster center as the position of the particle. The optimal cluster center was obtained by PSO algorithm optimizing and the sample data were clustered using minimum distance criterion. The comparison results between cluster and PSO-based cluster show that the proposed method can get the proper cluster result and provides a new approach to clothing fabrics selection and evaluation.