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About Article - Applications of Artificial Neural Networks in Chemical Engineering
The document discusses applications of artificial neural networks in chemical engineering. It describes different types of neural networks that have been effective in applications, including feedforward nets, recursive nets, and radial basis function nets. It then provides four detailed examples of applying neural networks to problems in chemical engineering, such as fault detection, polymer quality prediction, data rectification, and process modeling and control.
Detailed Information
| Author: | ['Evelin Koch'] |
|---|---|
| Publication Year: | 2018 |
| Pages: | 20 |
| Language: | English |
| Format: | |
| Price: | FREE |
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