遗传算法用于结晶过程动力学参数辩识

遗传算法是一类随机优化方法。常被用于解决复杂的优化问题，基于群体的搜索，重组和变异是遗传算法区别于其他优化方法的主要特征。文章中将遗传算法应用于过饱和溶液Ｌｉ２Ｏ．３Ｂ２Ｏ３－Ｈ２Ｏ体系结晶过程动力学参数辨识，确定了结晶反应速率常数、热力学平衡浓度和表观反应级数。

APPLICATIONS OF GENETIC ALGORITHMS IN DYNAMIC PARAMETER RECOGNITION OF CRYSTALLINE PROCESS

Genetic algorithms comprise a family of stochastic optimization strategies which are often applied to solve complex optimization problems. The population based search,recombination and mutation distinguish the genetic algorithms from other optimization techniques. In this paper, genetic algorithms are employed to recognize the dynamic parameters of crystalline process in supersaturated solutions of Li 2O\53B 2O 3 H 2O system. The recognized parameters are crystalline reaction rate, thermodynamic equilibrium concentration and apparent reaction order. The factors, including population size, recombination rate and mutation rate, which influence the convergence of genetic algorithms have been discussed. The results show that variations of these parameters must not always improve the trial solutions. In addition, the finding of high accuracy crystalline dynamic equation shows that genetic algorithm can be used as a robust technique for parameter recognition.