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以基本遗传算法为基础,引入多重退火交叉,并以多种变异模式竞争取代单一的变异策略,以随着遗传代数和个体适应度动态调节的交叉和变异概率代替固定不变的交叉和变异概率,提出了一种改进的遗传算法;用于研究包含复杂组分、同时进行多种反应的催化裂解反应集总动力学,并与传统的算法比较,证明改进的遗传算法可迅速、准确获得有物理意义的动力学参数优化值,是研究复杂反应动力学的有效数值工具。
Based on the basic genetic algorithm, multiple annealing crossovers are introduced, and a single mutation strategy is replaced by a variety of mutation modes to replace the fixed crossover and mutation probabilities with the crossover and mutation probabilities of the dynamic adjustment of genetic algebra and individual fitness , An improved genetic algorithm is proposed. It is used to study the luminescence kinetics of catalytic pyrolysis reactions involving complex components and multiple reactions at the same time. Compared with the traditional algorithms, the improved genetic algorithm can be quickly and accurately obtained Physical significance of the optimization of kinetic parameters, is an effective numerical tool to study complex reaction kinetics.