This dissertation presents the studies of genetic algorithms (GA) based model structure and parameters conjunct identification, PID optimization, and the engineering application method.
本论文是基于遗传算法(GA)的模型结构和参数共同辨识、PID参数的优化整定和工程应用方法的研究。
Based on the optimization model and the work process of genetic algorithms, the program was written to calibrate the groundwater model.
基于优化模型和遗传算法的运算过程，编写计算程序，实现地下水数学模型的自动识别。
Then optimization model with the membership degree is constructed. It is solved by using genetic algorithms with dynamical castigatory function.
然后结合隶属度变量构建优化模型，利用具有动态惩罚函数的遗传算法求解，计算得到各方案的所属类别。
Scramjet combustor design optimization for a test scramjet model engine is conducted by employing genetic algorithms, and an optimal design much better than original design is obtained.
采用遗传算法对某试验超燃冲压模型发动机的燃烧室构型参数进行了优化设计，所得方案的性能大大优于实际方案。
Therefore, the mathematic model for optimization disinfection was set up, and the hybrid genetic-simulated annealing algorithm was used for solution.
为此，建立了优化消毒数学模型，并采用遗传—模拟退火混合算法对其进行求解。
The key kinetic parameters of the new model were adjusted by using a genetic algorithm optimization methodology to improve ignition timings prediction.
另外，采用遗传优化技术对模型动力学参数进行调整。
The key kinetic parameters of the new model were adjusted by using a genetic algorithm optimization methodology to improve ignition timings prediction.
另外，采用遗传优化技术对模型动力学参数进行调整。
应用推荐