摘要
研究计算机数学建模中改进遗传算法与最小二乘法的具体应用。针对基本遗传算法中存在的数据冗余问题,提出了一种改进遗传算法,结合最小二乘法建立计算机数学模型,以更好的应对数据变化。对具体的问题进行计算机数学建模,并进行验证,结果表明改进后的遗传算法具有一定的辨识能力,寻找最优,大大提高了工作效率。利用MATLAB软件求解方程组,确定参数的使用范围,解决估算参数范围和辨识问题。仿真结果证明改进后的遗传算法与最小二乘法结合后建立数学模型,大大增加了个体搜索空间,比基本遗传算法提高了90%的运算率。
aiming at the data redundancy problem existing in the basic genetic algorithm,an improved genetic algorithm was adopted,and a computer mathematical model was established by combining the least square method to better cope with the changes of data. Through the establishment of two problems,the corresponding mathematical model is established,on the discussion aiming at specific problems,it is concluded that the improved genetic algorithm and least squares method combined with the application,there is a certain advantage in the computer mathematical modeling,parameter,the identification problem will happen in the long coding,through crossover and mutation genetic algorithm can make the individual search space increases,thus solving the problem of system identification.
作者
余航
YU Hang(College of General Education,Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China)
出处
《电子设计工程》
2020年第1期15-18,共4页
Electronic Design Engineering
基金
国家自然科学基金资助项目(11401399)
关键词
数学建模
改进遗传算法
最小二乘法
拟合
mathematical modeling
improved genetic algorithm
least square method
fitting
