摘要
催化精馏合成碳酸二甲酯能够显著提高反应物碳酸丙烯酯的转化率。这里采用径向基神经网络建立某些操作条件与碳酸丙烯酯的转化率之间的模型,并采用遗传算法优化操作条件。优化结果得到试验验证。
Catalyst distillation is an efficient method to produce Dimethyl Carbonate （DMC）. In this paper, an RBF Neural Network model of the process is built according to the experimental data. Based on the model, the optimized operation parameters are obtained by the genetic algorithms. The optimized operation condition is proved by experiment.
出处
《东华大学学报（自然科学版）》
CAS
CSCD
北大核心
2006年第4期47-50,共4页
Journal of Donghua University(Natural Science)
关键词
碳酸二甲酯
催化精馏
径向基神经网络
遗传算法
最优操作条件
dimethyl carbonate, catalyze distillation, RBF neural network, genetic algorithms, optimized operation parameters
