Document Type : Scientific extension

Authors

1 Instructor . Department of Mechanics and Materials Engineering. Birjand University of Technology . Birjand. Iran

2 Ph.D. Student. Department Engineering .Semnan University. Semnan. Iran

3 PhD. student. Department of Engineering. Semnan University. Semnan. Iran

4 M.Sc. Student. Department of Engineering . Urmia University. Tehran. Iran

Abstract

 In this paper, Extreme Learning Machine method is used to model the rate of material transfer as an effective parameter in process speed and surface quality. Using neural network model of Extreme Learning Machine, the mean squared error (MSE) for the material transfer rate in the learning data is 0.000,387 and in the test data is 0.001,7. While, the mean error squared for the average reset layer thickness, calculated in the learning data, was 0.000,214 and in the test data was 0.001,7. The proposed algorithm of Extreme Learning Machine with experimental results has high accuracy in predicting a process output parameters.

Keywords

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