基于MATLAB的RBF神经网络的一种应用

提出了一种用于预报转炉炼钢终点磷含量的智能方法。在该方法中，采用RBFNN方法，对转炉冶炼过程进行建模与仿真。MATLAB中的神经网络工具箱是进行神经网络系统分析与设计的有力工具。RBF神经网络以其计算量小，学习速度快，不易陷人局部极小等诸多优点为系统辨识与建模提供了一种有效的手段。将二者结合起来，解决转炉冶炼中的建模问题，取得了令人满意的结果。

APPLICATION OF MATLAB-BASED RBF NEURAL NETWORK

it proposed an intelligent method for forecasting phosphorus content of converter smelting end. By adopting RBFNN method in the intelligent method, it carried on modeling and simulating for the converter smelting process. MATLAB neural network toolbox is a powerful tool which can be used in the neural network system analyzing and designing. RBF Neural Network has small computational burden and fast learning rate and is not liable to be trapped by local minimal points ete. So it is an effective means to identify and model a system. In this paper, the neural network toolbox in MATLAB and RBF neural network are combined to solve the problem of modeling the converter smelting process and the result was excellent.