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综合运用了一种改进的遗传算法和自适应建模技术对燃气轮机的精确特性进行寻优获取.引入自适应机制优化交叉和变异算子,同时引入模拟退火算法,使改进遗传算法能很快接近最优解,并能跳出局部最优的陷阱,在保证解的质量的同时提高了收敛的速度.针对以往自适应模型中未考虑测量参数间的线性相关性和不同的传感器测量精度对目标函数的影响等问题,采用加权方法建立了较为完备的燃气轮机自适应数学模型,应用改进遗传算法获取燃气轮机部件的精确特性,实例计算结果表明:模拟退化改进遗传算法进行的自适应建模效果更好.
A kind of improved genetic algorithm and adaptive modeling technique are used synthetically to acquire the exact characteristics of gas turbine.An adaptive mechanism is introduced to optimize the crossover and mutation operator and the simulated annealing algorithm is introduced so that the improved genetic algorithm can be quickly approached Optimal solution and can jump out of the local optimal trap to improve the convergence rate while ensuring the quality of the solution.Aiming at the problem that the linear correlation of the measured parameters and the different sensor measurement accuracy are not considered in the previous adaptive model, , The gas turbine adaptive mathematical model is established by using the weighted method, and the precise characteristics of the gas turbine components are obtained by using the improved genetic algorithm. The calculation results of the examples show that the adaptive degradation of the modified genetic algorithm is better.