河南农业大学学报2018，Vol.52Issue(3)：371-376,6.
基于计算机智能算法的纤维素生物质醇解优化
Optimization of alcoholysis of cellulosic biomass based on computer intelligent algorithm
摘要
Abstract
Using the computer intelligent algorithm as tools,the optimization of methyl levulinate production from cellulosic biomass wheat straw by alcoholysis was studied.The effects of reaction temperature,reaction time and amount of catalyst on the yield of methyl levulinate were investigated,and the Box-Behnken experiment was carried out under the condition of the temperature of 170～190 ℃,the reaction time of 1～5 h,and the catalyst amount of 0.3～0.7 g.Based on the experimental data,the artificial neural network was constructed and optimized,and the results showed that the BP neural network optimized by genetic algorithm had more accurate prediction ability.On the basis,optimization using genetic algorithm was further performed,and the optimal reaction condition of alcoholysis could be obtained,which are reaction temperature of 170 ℃,reaction time of 4.4 h,and amount of catalyst 0.64 g.Under this condition,the yield of ML reached to 51.1％,close to the predicted value.This study indicates that using the intelligent algorithm is an effective method to optimize the alcoholysis process of cellulosic biomass.关键词
人工神经网络/遗传算法/秸秆/醇解Key words
artificial neural network/genetic algorithms/wheat straw/alcoholysis分类
农业科技引用本文复制引用
吴彦国,徐桂转,王晨..基于计算机智能算法的纤维素生物质醇解优化[J].河南农业大学学报,2018,52(3):371-376,6.基金项目
河南省基础与前沿技术研究项目(162300410007) （162300410007）
