文件名称:accessory_parameter
介绍说明--下载内容均来自于网络,请自行研究使用
lingjian.m-----蒙特卡罗方法
lingjian.m使用零件初始值,用蒙特卡罗方法算出总费用。其中使用了自己编制的正态分布随机数发生器产生正态分布随机数。lingjian.m是对蒙特卡罗方法的一次练习。
accyouhua为标定值的函数,而lingjian不是一个函数,在其中已给出了一组标定值的值。
退火确定标定值/unitanneal()----模拟退火
连续型多个变量组合优化问题
这是对模拟退火方法的一次练习,结果证明模拟退火确实是一个行之有效的方法。
当参数选择较好时(一般也伴随着运行时间的加长),模拟退火的结果较好,然而用MATLAB的FMIMCON()一般可达到更高的精度。-lingjian.m----- Monte Carlo method
lingjian.m part the initial value, using the Monte Carlo method to calculate the total cost. The use of the preparation of their own normal distribution random number generator to produce a normal distribution of random numbers. lingjian.m yes to the first practice of the Monte Carlo method.
accyouhua calibration function, and lingjian is not a function, which has given the value of a set of calibration values .
Annealing to determine the calibration value/unitanneal ()---- Simulated Annealing
Combinatorial optimization problem of continuous multiple variables
This is a practice of simulated annealing method, the results show that simulated annealing is an effective method.
Parameter selection is better (usually accompanied by longer running time) the results of simulated annealing, however the MATLAB FMIMCON () generally achieve higher accuracy.
lingjian.m使用零件初始值,用蒙特卡罗方法算出总费用。其中使用了自己编制的正态分布随机数发生器产生正态分布随机数。lingjian.m是对蒙特卡罗方法的一次练习。
accyouhua为标定值的函数,而lingjian不是一个函数,在其中已给出了一组标定值的值。
退火确定标定值/unitanneal()----模拟退火
连续型多个变量组合优化问题
这是对模拟退火方法的一次练习,结果证明模拟退火确实是一个行之有效的方法。
当参数选择较好时(一般也伴随着运行时间的加长),模拟退火的结果较好,然而用MATLAB的FMIMCON()一般可达到更高的精度。-lingjian.m----- Monte Carlo method
lingjian.m part the initial value, using the Monte Carlo method to calculate the total cost. The use of the preparation of their own normal distribution random number generator to produce a normal distribution of random numbers. lingjian.m yes to the first practice of the Monte Carlo method.
accyouhua calibration function, and lingjian is not a function, which has given the value of a set of calibration values .
Annealing to determine the calibration value/unitanneal ()---- Simulated Annealing
Combinatorial optimization problem of continuous multiple variables
This is a practice of simulated annealing method, the results show that simulated annealing is an effective method.
Parameter selection is better (usually accompanied by longer running time) the results of simulated annealing, however the MATLAB FMIMCON () generally achieve higher accuracy.
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下载文件列表
accessory_parameter\accyouhua.m
...................\lingjian.m
...................\normal.m
...................\说明.txt
...................\退火确定标定值\accept.m
...................\..............\accessory.mat
...................\..............\funacc.m
...................\..............\generatenew.m
...................\..............\unitanneal.m
...................\退火确定标定值
accessory_parameter
...................\lingjian.m
...................\normal.m
...................\说明.txt
...................\退火确定标定值\accept.m
...................\..............\accessory.mat
...................\..............\funacc.m
...................\..............\generatenew.m
...................\..............\unitanneal.m
...................\退火确定标定值
accessory_parameter