Abstract: Curve fitting method of BP neural network was introduced and applied in the model of the dispersion of calcite crystals by MATLAB tools. The results show that BP algorithm has high forecasting capacity and good generalization capacity in three areas: the map of curve fitting, the deviation curve and the error norm. BP neural network can automatically identify mathematical model, which has higher precision, and its principle is relatively simple. So it is a very good tool for complex input-output system.

Key words: Calcite , BP neural network , MATLAB

摘要： 介绍BP算法神经网络曲线拟合方法,并借助MATLAB工具箱函数将它运用于方解石色散特性研
究,通过拟合效果图,误差曲线,误差范数反映BP神经网络的优越性,体现BP算法较高的预测能力和良好的泛化能
力,并且可以自动地确定数学模型,精确度高,原理也较简单,尤其对复杂的输入输出系统具有更好的效果。

关键词: 方解石 , BP神经网络 ,  MATLAB