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Process optimization using neural networks

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4 Author(s)
Yi Yang ; Dept. of Comput. Sci., Cincinnati Univ., OH, USA ; Cheng, Yizong ; Renhong Zhao ; Govind, R.

Optimization of chemical processes can result in decreased energy consumption, improved productivity, better product quality, and generally increased profits. Most chemical plants achieve optimal operation by gradually varying process conditions experimentally and exploring a localized feasible region around the current operating point. Major concerns are cost and time involved in attempting to achieve "optimal operation". This paper presents a systematic methodology using neural networks to improve the efficiency of a sequential search process for achieving optimal process operating conditions. An example, developed by Ultramax Corporation, Cincinnati, is presented to illustrate the approach

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:7 )

Date of Conference:

27 Jun-2 Jul 1994