文件名称:matlab-accessory_parameter
- 所属分类:
- 人工智能/神经网络/遗传算法
- 资源属性:
- [Matlab] [源码]
- 上传时间:
- 2013-04-06
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- 4kb
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- 0次
- 提 供 者:
- 吴**
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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.
氀椀渀最樀椀愀渀.m Part initial value, using the Monte Carlo method to calculate the total cost. The preparation of their own normal distribution random number generator to generate normally distributed random numbers. lingjian.m is the first practice of the Monte Carlo method.
accyouhua calibration value the function lingjian not a function, which gives the value of a set of calibration values.
Annealing to determine the calibrated value/unitanneal ()---- Simulated Annealing
吀栀攀 continuous multiple variables combinatorial optimization problems
吀栀椀猀 is an exercise of the simulated annealing method, the results show that the simulated annealing is an effective method.
圀栀攀渀 the parameter selection is better (generally accompanied by a longer running time), simulated annealing results, however using 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.
氀椀渀最樀椀愀渀.m Part initial value, using the Monte Carlo method to calculate the total cost. The preparation of their own normal distribution random number generator to generate normally distributed random numbers. lingjian.m is the first practice of the Monte Carlo method.
accyouhua calibration value the function lingjian not a function, which gives the value of a set of calibration values.
Annealing to determine the calibrated value/unitanneal ()---- Simulated Annealing
吀栀攀 continuous multiple variables combinatorial optimization problems
吀栀椀猀 is an exercise of the simulated annealing method, the results show that the simulated annealing is an effective method.
圀栀攀渀 the parameter selection is better (generally accompanied by a longer running time), simulated annealing results, however using MATLAB FMIMCON () generally achieve higher accuracy.
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下载文件列表
蒙特卡罗方法 退火确定标定值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
蒙特卡罗方法 退火确定标定值accessory_parameter