论文部分内容阅读
应用遗传算法估算溶液热力学模型参数,并对标准遗传算法中的变异策略和竞争方式作了适当的改进,得到改进的遗传算法。举DMF(二甲基甲酰胺)+water体系的溶液热力学模型参数的估算为例,并与POWELL法比较。计算结果表明,遗传算法比POWELL法具有更强的寻优能力,而本文所提出的改进的遗传算法比标准遗传算法的寻优速度明显较快,对解决溶液热力学模型这类复杂的非线性函数的参数估算问题,本文所提出的改进的遗传算法是一种较好的寻优算法。
The parameters of solution thermodynamic model are estimated by using genetic algorithm. The mutation strategy and competition mode of standard genetic algorithm are improved properly, and the improved genetic algorithm is obtained. The parameters of the solution thermodynamic model in DMF (dimethylformamide) + water system are estimated and compared with the POWELL method. The results show that genetic algorithm has better searching ability than POWELL method, and the improved genetic algorithm proposed in this paper is faster than the standard genetic algorithm in finding the optimum speed. To solve the complicated nonlinear function of solution thermodynamic model The problem of parameter estimation, the improved genetic algorithm proposed in this paper is a better optimization algorithm.