基于模糊神经网络的切削参数预测方法

提出了一种基于模糊神经网络的数据挖掘算法,将模糊理论与神经网络技术结合,避免了单纯的神经网络结构复杂、网络训练时间长、结果表示不易理解等不足。经过模糊神经网络的建立和训练可达到精度要求。将试验值、单纯神经网络及支持向量机的预测结果进行比较,可以得出如下结论:当模糊神经网络的隶属度函数中的参数及神经网络连接权值的初始值合理时,其学习算法的精度高,收敛性好。

Cutting Parameter Prediction Method Based on Fuzzy Neural Network

To avoids the simple neural network structure is complex, the network training time is long, lack of und~r- standable representation of results, this paper presents a data mining algorithm based on fuzzy neural network combining the fuzzy theory with neural network technology. After the fuzzy neural network is established and training can meet precision requirement. The test data, simple neural network and support vector machine forecast results are compared, when fuzzy neural network membership function of the parameters and initial values of connection weights of the neural network are rea- sonable, and its learning algorithm with high accuracy, good convergence.