摘要
针对常规神经网络和模糊神经网络的不足,介绍了一种具有快速算法的补偿模糊神经网络,并根据电火花加工的工艺特点及其复杂性,建立了基于补偿模糊神经网络的电火花加工工艺效果预测模型,可实现指定加工条件下的工艺效果预测。仿真结果显示了其良好的预测精度,其性能优于常规模糊神经网络。
In order to overcome the drawbacks of conventional Artificial Neural Networks (ANN) and Fuzzy Neural Networks (FNN), the Compensatory Fuzzy Neural Network (CFNN) with fast learning algorithms was introduced. Then the predictive model of techno- logical effect for EDM based on CFCC was developed according to the technological characteristics of EDM and its complexity, and it can precisely predict the technological effect for specified machining conditions. The simulation results show that the model has good predictive precision and is superior in the performance to the ones based on the conventional FNN.
出处
《微计算机信息》
北大核心
2007年第19期307-308,304,共3页
Control & Automation
