关键词: 前向神经网络, 粒子群优化算法, 免疫系统, 抗体抑制

Abstract: Feedforward neural network can be used to detect structural damage，but the gradient descent method in traditional BP algorithm is vulnerable to local optimum.Particle Swarm Optimizer（PSO） can be capable of searching optimum in global scope，by introducing clone suppression in immune systems into PSO to maintain the diversity of particles.The hybrid algorithm（ImPso） can be used to train feedforward neural network.The computer simulation results show that the performance of neural network with the hybrid algorithm（ImPso） is better than the performance with traditional gradient descent method.

Key words: feedforward neural nework, Particle Swarm Optimization（PSO）, immune systems, clone suppression