基于神经网络和遗传算法的C4烯烃合成问题

C4 Olefin Synthesis Problem Based on Neural Network and Genetic Algorithm

乙醇耦合制备C4烯烃是化工领域一个重要的制备反应,优化该反应的工艺条件对提高化工产业生产技术和降低生产成本具有重要作用。根据一系列乙醇在不同催化剂组合和温度下催化耦合制备C4烯烃的实验数据,探究催化剂组合与温度对C4收率的影响,并寻找最优的催化剂组合及温度条件,来最大化C4烯烃的收率。本文使用了神经网络对实验数据进行回归分析,得到催化剂组合及温度对C4烯烃收率的影响规律。接着使用遗传算法求解收率最大时的生产条件,在此条件下最大的C4烯烃收率为0.9 206。以数学建模的方式求解,可以从理论上指导实验方向,提高实验效率,具有实用性。

Ethanol coupling to produce C4 olefins is an important preparation reaction in the chemical industry. Optimizing the process conditions of this reaction has an important effect on improving the production technology of the chemical industry and reducing production costs. In this paper, based on a series of experimental data of catalytically coupling production of C4 olefins by ethanol under different catalyst combinations and temperatures, the effect of catalyst combination and temperature on the yield of C4 is explored, and the optimal combination of catalysts and conditions are found to obtain the maximum C4 olefins yield. In this paper, a neural network is used to perform regression analysis on the experimental data,and the influence of catalyst combination and temperature on the yield of C4 olefins is obtained. Next, the genetic algorithm was used to solve the production conditions at the maximum yield, and the maximum C4 olefin yield was 0.9 206. This paper uses mathematical modeling to solve the problem, which can theoretically guide the direction of the experiment, improve the efficiency of the experiment, and is practical.