Precision Obtained Using an Artificial Neural Network for Predicting the Material Removal Rate in Ultrasonic Machining

Precision Obtained Using an Artificial Neural Network for Predicting the Material Removal Rate in Ultrasonic Machining

The present study proposes a back propagation artificial neural network (BPANN) to provide improved precision for predicting the material removal rate (MRR) in ultrasonic machining. The BPANN benefits from the advantage of artificial neural networks (ANNs) in dealing with complex input-output relati...

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Bibliographic Details
Main Authors: Gaoyan Zhong, Min Kang, Shoufeng Yang
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Applied Sciences
Subjects:
artificial neural network
regression techniques
modelling precision
material removal rate
ultrasonic machining
Online Access:https://www.mdpi.com/2076-3417/7/12/1268

Internet

https://www.mdpi.com/2076-3417/7/12/1268

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