Study on the simulation control of neural network algorithm in thermally coupled distillation
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Abstract (arXiv)
Thermally coupled distillation is a new energy-saving method, but the traditional thermally coupled distillation simulation calculation process is complicated, and the optimization method based on the traditional simulation process is difficult to obtain a good feasible solution. The neural network algorithm has the advantages of fast learning and can approach nonlinear functions arbitrarily. For the problems in complex process control systems, neural network control does not require cumbersome control structures or precise mathematical models. When training the network, only the input and output samples it needs are given, so that the dynamics of the system can be controlled. Performance is approaching. This method can effectively solve the mathematical model of the thermally coupled distillation process, and quickly obtain the solution of the optimized variables and the objective function. This article summarizes the research progress of artificial neural network and the optimization control of thermally coupled distillation and the application of neural network in thermally coupled distillation.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 2 of its 78 references that are in the map. First posted on arXiv 6 Feb 2021.
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2 of 78 references.
References · 2
- 2018Nonparallel Emotional Speech Conversioncited by 17
- 2017Distributionally Robust Games: f-Divergence and Learningcited by 5
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Citing papers per year: 2021: 1.
1 paper.