乙苯脱氢反应器的ANN模型及其工况模拟与优化

SIMULATION AND OPTIMIZATION OF AN ETHYLBENZENE DEHYDROGENATION REACTOR USING ARTIFICIAL NEURAL NETWORKS(ANNS)

提出一种不同于传统数学建模的具有智能功能的化工过程系统建模及优化方法一人工神经元网络（ANN）模型法，并对苯乙烯生产中的乙苯脱氢反应器作了模拟及实际生产调优．结果表明，ANN模型法用于过程模拟具有其他传统数学模型所不能比拟的自适应性和自学习功能；用于过程调优时，寻优速度快，尤其是对于多目标优化问题，更能显示出其优越性．

An ANN model is established for simulation and optimization on an ethylbenzene dehydrogenation reactor. It is showed that the self-learning and adaptive ability of the model makes it useful for simulation and optimization of multiple objective process.