A machine learning approach to estimate magnetorheological suspension composition based on magnetic field dependent-rheological properties
This paper presents an inverse model of magnetorheological (MR) suspensions to predict the compositions as a function of magnetic field-dependent rheological properties using the feedforward neural network (FFNN) model. Although many variations of MR suspension compositions have been published, the...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Published: |
IOP Publishing Ltd.
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/95644/ http://dx.doi.org/10.1088/1361-665X/ac1d92 |
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