Nonlinear Chemical Process Monitoring And Fault Detection Based On Modified Lstm Model
With the development of the chemical industry, fault detection of chemical process has become hard challenge due to the high-dimensional data and complex chemical process and increasing number of equipment. The standard feedforward neural network is not particularly effective at solving these issues...
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| Format: | Monograph |
| Language: | English |
| Published: |
Universiti Sains Malaysia
2022
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| Online Access: | http://eprints.usm.my/55494/1/Nonlinear%20Chemical%20Process%20Monitoring%20And%20Fault%20Detection%20Based%20On%20Modified%20Lstm%20Model.pdf http://eprints.usm.my/55494/ |
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