Optimizing operating conditions based on ANN and modified GAs
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Abstract In this paper, an effective method based on artificial neural networks (ANN) and genetic algorithms (GAs) was suggested for modeling the process with unknown or complex mechanisms and optimizing its operating conditions consecutively. Furthermore a modified GA (MGA) with adaptive mutation range was proposed to search the optimal location more quickly. The satisfactory results of this investigation demonstrated the feasibility and effectiveness of the suggested method, and particularly showed that MGA could find the optimal values more quickly than the conventional GAs.
[1] Simant R. Upreti,et al. Optimal design of an ammonia synthesis reactor using genetic algorithms , 1997 .
[2] Patrick Sebastian,et al. Global optimization of a dryer by using neural networks and genetic algorithms , 1999 .
[3] B. Irie,et al. Capabilities of three-layered perceptrons , 1988, IEEE 1988 International Conference on Neural Networks.
[4] Chris Aldrich,et al. Empirical modelling of chemical process systems with evolutionary programming , 1998 .