摘要
针对谷氨酸发酵过程建模中变量取值范围扩大时，二进制遗传算法存在收敛速度和精度的矛盾，研究了改进的浮点遗传算法．仿真结果表明：该改进算法能克服二进制遗传算法的缺点，不仅在收敛精度和速度上都有明显的改进，且效率很高．具有工程实际应用前景．
In the light of the contradiction between the convergence speed and accuracy caused by the string length of the binary encoding when the range of the variables increases in the process modelling of fermentation of glutamic acid, a new improved GA_floating genetic algorithm is discussed. The simulation results have indicated that the new algorithm can cope with the shortcoming of the binary GA, providing not only its great improvement in accuracy and search speed but also its high efficience, and that the new algorithm has good potential for the engineering applications.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
1998年第5期34-38,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
广东省自然科学基金
关键词
浮点遗传算法
乘积系数
建模
谷氨酸
发酵
floating genetic algorithm
multiplication factor
modelling
process of fermentation of glutamic acid
