Study on flatness pattern recognition based on intelligent optimal radial basis function neural network

In order to deal with the problem that the usual flatness pattern recognition methods based on neural network have some flaws which restrict their applications,i.e.,lower precision for the obtained networks,lower velocity for both on-line recognition and complex network modeling,a kind of flatness pattern recognition based on intelligent optimal radial basis function (RBF) neural network was proposed.In the process of modeling the neural network based on some training data,an improved particle swarm optimization algorithm was proposed to optimize both the number of network nodes and the value of network parameters.Therefore,the approach has simpler structure and better generalization than before.The simulation experiment results showed that the approach was effective and could increase the precision of flatness control.