搜索资源列表
遗传算法（实数编码）
- 遗传算法的源代码，不错，希望与大家共同分享，谢谢1-genetic algorithm source code, good, and he hopes to share with you, thank you a
遗传算法的源代码
- 基于实数编码遗传算法源代码,该程序很好用,已经调试通过-real-coded genetic algorithm source code, the procedure is useful, has been through testing
float_ga
- 用matlab编写的实数编码遗传算法，非常的好-using Matlab prepared by the real-coded genetic algorithm, a very good
GeneticAlgorithmxujinpeng
- 这个算法采用遗传算法（实数编码），可以找到带有约束和无约束函数的最大值 。遗传算法的表现也通过后代的数量绘制出来。-This function can find the maximum of constrained and unconstrained problems with using of genetic algorithm (real coding). Also the performance of GA is plotted vs. the number of generations
GA_Ashi
- 用Delphi实现的遗传算法实数编码的源程序，相应的参数根据需要进行设定。-Using Delphi to achieve real-coded genetic algorithm s source code, the corresponding parameter settings as needed.
PID-GAs
- 遗传算法的PID调节 题目：已知 ，利用GA 寻优PID参数，其中K=1，T=2， ，二进制/实数编码，位数不限，M，Pc，Pm自选，性能指标 ，Q=100为仿真计算步长。-PID regulation of genetic algorithms Title: known, the use of PID parameters of GA optimization, in which K = 1, T = 2,, binary/real-coded, not limited to the me
gaPID
- 采用遗传算法优化传统PID控制，选取了合适的优化函数，采用实数编码-Genetic algorithm to optimize the traditional PID control, select the appropriate optimization function using real-coded
Matlab_BP
- 于BP网络的权值优化是一个无约束优化问题，而且权值要采用实数编码，所以直接利用Matlab遗传算法工具箱。以下贴出的代码是为一个19输入变量，1个输出变量情况下的非线性回归而设计的，如果要应用于其它情况，只需改动编解码函数即可。-BP network weights optimization is a constrained optimization problem, and the right value to real-coded, so the direct use of the Matl
GA-MATLAB
- 遗传搜索算法，实数编码的源程序。适合各种版本的 matlab-Genetic search algorithm matlab
real-code
- 实数编码实现遗传算法，变量为多维，目标函数为一维，适合初学者-Real-coded genetic algorithms, multi-dimensional variables, the objective function is one-dimensional, suitable for beginners
Realcoded
- 二进制编码和实数编码的遗传算法，代码非常详尽，略有难度。-Binary coding and real-coded genetic algorithm, very detailed.
SGA
- 自编的基于实数编码的遗传算法源程序（fortran） ，用于搜索最小值-Self-based real-coded genetic algorithm source code (fortran), used to search for the minimum
00153586PPC-RAGA
- 基于实数编码的加速遗传算法可以对优化问题进行求解(raga Used for data culling and screening of high quality data)