基于神经网络方法的包装件非线性特性识别的研究

结合模糊集合理论，将结构化神经网络方法用于包装件缓冲垫层非线性特性识别问题．对于两种典型的包装件缓冲垫层材料模型的模拟识别结果表明，据此方法可以较好地获得其非线性特性．模糊自适应技术的引入，提高了网络训练速度，减少了对于训练参数的人为干预，使得结构化神经网络方法更适于实际应用．

A STUDY OF IDENTIFICATION OF NONLINEAR CHARACTERISTICS IN CUSHIONING PACKAGING BASED ON NEURAL NETWORKS

The structural neural network method with fuzzy adaptive controlis applied to the identification of nonlinear characterisics in packaging cushionings in this paper. The simulated results on the two typical models of packaging cushioning materials show that the nonlinear characteristics can be identified perfectly. The combination of the structural neural network method with fuzzy adaptive techniques increases the training speed of the network, reduces the artificial interference to parameters of the network, and enables the structural neuralnetwork method to be more applicable in practice.