Aiming at the complexity of the glutamic acid fermentation process, a neural network dynamic model of the fermentation process was established. The improved differential evolutionary algorithm (DEA) was used to the mu...
详细信息
ISBN:
(纸本)9781424421138
Aiming at the complexity of the glutamic acid fermentation process, a neural network dynamic model of the fermentation process was established. The improved differential evolutionary algorithm (DEA) was used to the multi-variables optimal control of the fermentation process and the optimal control trajectories of operating variables were found out. Some improvements of the primitive DEA were made by the means of randomly selecting the mutation factor and the re-initialization of the individuals in the population on a suitable time, so that it could solve the constrained optimization effectively and avoid the problem caused by premature. Simulation results show the proposed method is effective.
Aiming at the complexity of the glutamic acid fermentation process, a neural network dynamic model of the fermentation process was established. The improved differential evolutionary algorithm (DEA) was used to the mu...
详细信息
Aiming at the complexity of the glutamic acid fermentation process, a neural network dynamic model of the fermentation process was established. The improved differential evolutionary algorithm (DEA) was used to the multi-variables optimal control of the fermentation process and the optimal control trajectories of operating variables were found out. Some improvements of the primitive DEA were made by the means of randomly selecting the mutation factor and the re-initialization of the individuals in the population on a suitable time, so that it could solve the constrained optimization effectively and avoid the problem caused by premature. Simulation results show the proposed method is effective.
In this article, some methods are proposed for enhancing the converging velocity of the COA (chaos optimization algorithm) based on using carrier wave two times, which can greatly increase the speed and efficiency of ...
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In this article, some methods are proposed for enhancing the converging velocity of the COA (chaos optimization algorithm) based on using carrier wave two times, which can greatly increase the speed and efficiency of the first carrier wave’s search for the optimal point in implementing the sophisticated searching during the second carrier wave is faster and more accurate. In addition, the concept of using the carrier wave three times is proposed and put into practice to tackle the multi-variables opti- mization problems, where the searching for the optimal point of the last several variables is frequently worse than the first several ones.
In this article, some improving methods are put forward for the converging velocity of the COA (chaos optimization algorithm) based on carrying wave two times, which can greatly increase the velocity and efficiency of...
详细信息
ISBN:
(纸本)9789806560604
In this article, some improving methods are put forward for the converging velocity of the COA (chaos optimization algorithm) based on carrying wave two times, which can greatly increase the velocity and efficiency of the first time to carry wave to search for the optimal point, implementing the sophisticated searching during secondly carrying wave more quickly as well as accurately. In addition, the concept of three-time carrying wave is put forward and is put into practice, to tackle the multi-variables optimization problems where the searching for the optimal position of the last several variables is frequently worse than the first several ones.
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