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- W2382309568 abstract "To predict and control cutting force effectively is very important for machining process to achieve high quality and low cost.Based on the feed-forward multi-layer neural networks,trained by the error back-propagation(BP) algorithm,the predicting cutting force program by using oriented-object language Visual C++ has been built up.In order to make calculating fast and accurate,two methods of optimization,the conjugated gradient and Quasi-Newton,have been applied to the training process of the network to avoid the main problems of supersaturation and local minimum.The experimental data of milling and grinding of two kinds of materials which are difficult to machine have been applied to the program.The results indicate that the maximum relative errors obtained by the traditional empirical formula method and the artificial neural network method are(24.9%) and 2.01% respectively.The approach to the prediction of cutting force with the help of artificial neural network is valuable for application." @default.
- W2382309568 created "2016-06-24" @default.
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- W2382309568 date "2005-01-01" @default.
- W2382309568 modified "2023-09-25" @default.
- W2382309568 title "Prediction of cutting force using BP artificial neural network" @default.
- W2382309568 hasPublicationYear "2005" @default.
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