Heat integration of the azeotropic distillation system with ANN and GA

In this paper, an effective method with artificial neural networks (ANN) and a genetic algorithm (GA) was suggested for modeling the azeotropic distillation system with unknown or complex mechanisms and optimizing its operating parameters to save energy. The satisfactory results of this investigatio...

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Bibliographic Details
Published inProceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527) Vol. 2; pp. 1573 - 1577 vol.2
Main Authors Li Ying, Wang Yao, Wang Yan-min, Yao Ping-jing
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Artificial neural networks
Chemical industry
Energy consumption
Food industry
Fuel economy
Heat engines
Industrial economics
Mining industry
Modeling
Power generation economics
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Summary:In this paper, an effective method with artificial neural networks (ANN) and a genetic algorithm (GA) was suggested for modeling the azeotropic distillation system with unknown or complex mechanisms and optimizing its operating parameters to save energy. The satisfactory results of this investigation demonstrated the feasibility and effectiveness of the suggested method. Furthermore, the azeotropic distillation system after optimization results in reduction of heat use by 54.03%. Thus, the study provides means for further optimization of the azeotropic distillation system, and directs practical production for process optimization.
ISBN:0780372689
9780780372689
DOI:10.1109/WCICA.2002.1020851