搜索资源列表
optimizing
- 遗传算法寻优，解决规划中面临的求优问题。-optimization by UG
ga_bp
- 基于遗传算法寻优初始权值的BP神经网络建模，-Optimization based on genetic algorithm BP neural network modeling
SVM-feature-optimization_GA
- 基于遗传算法寻优初始权值的BP神经网络建模-BP neural network model based on genetic algorithm optimization initial weights
CharlesLiSVR1.2
- 支持向量回归机工具箱。自编。带有GUI界面和使用教程。基于PCA降维和遗传算法寻优-Support vector regression toolbox. Self. With a GUI interface and tutorials. PCA dimensionality reduction based and genetic algorithm optimization
TSP_GA
- 本代码是用matlab语言编写的利用遗传算法寻优求解TSP问题，遗传算法部分所有子函数均为手工编写，最后画出了仿真得到的最优路线图。-The program is written in matlab program to solve TSP problem by genetic alogrithm,and the genetic optimization part is all written by hand(not calling functions or tools).at last,I d
GAfitSim
- 遗传算法寻优基于SIMULINK的寻优算法-Genetic algorithm optimization
ga
- 简单的matlab编写的用遗传算法寻优的源码，可用，注释清楚，利于初学者学习使用-GA written by matlab, simple example, good for new learners,gogogo
GATestMe
- 经典遗传算法寻优，利用轮盘赌选择复制，利用合适的变异概率得到子代-Classical genetic algorithm optimization, the use of roulette Copy, using suitable mutation probability give offspring
chapter4
- 神经网络遗传算法函数极值寻优——非线性函数极值寻优(Neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking)
yichuan
- 解决路径寻优问题的遗传算法，经过相对路径寻优的问题进行改进的算法，提高算法运行速度(Genetic algorithm for solving path optimization problem)
改进的禁忌搜索算法
- 改进的禁忌搜索算法，求解路径寻优问题，相对传统的遗传算法，能够更精确求得全局最优解(Compared with the traditional genetic algorithm, the improved tabu search algorithm can solve the problem of path optimization, and can obtain the global optimal solution more accurately)
sample1
- 进行非线性规划问题及遗传算法的三个例子，引用了遗传算法(Three examples of nonlinear programming problems and genetic algorithms are presented)
GA
- 本算法为遗传算法示例程序，对函数进行寻优(it's a Genetic Algorithm program, used to realize the optimizing function)
chapter8 基于量子遗传算法的函数寻优算法
- chapter8 基于量子遗传算法的函数寻优算法(Chapter8 function optimization algorithm based on quantum genetic algorithm)
powerflowcalcut
- 基于遗传算法和非线性规划寻优混合算法的电力系统最优潮流计算(Optimal power flow calculation of power system based on hybrid algorithm of genetic algorithm and nonlinear programming optimization)
GA_UnaryMultimodalFunction
- 函数优化：单元多峰函数优化，带寻优过程性能图。(Function Optimization)
GA
- 遗传算法（Genetic Algorithms，简称 GA）是一种基于自然选择原理和自然遗传机 制的搜索（寻优）算法，它是模拟自然界中的生命进化机制，在人工系统中实现特定目 标的优化。遗传算法的实质是通过群体搜索技术，根据适者生存的原则逐代进化，最终 得到最优解或准最优解。它必须做以下操作：初始群体的产生、求每一个体的适应度、 根据适者生存的原则选择优良个体、被选出的优良个体两两配对，通过随机交叉其染色 体的基因并随机变异某些染色体的基因后生成下一代群体，按此方法使群体逐代进化， 直
chapter2
- 基于遗传算法和非线性规划的函数寻优算法;(Function Optimization algorithm based on genetic algorithm and nonlinear programming)
pso2
- 粒子群比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(It is more simple than the genetic algorithm rule. It doesn't have the crossover (Crossover) and the Mutati
ga
- 遗传算法的matlab实现，可以应用于各种寻优过程(The matlab implementation of genetic algorithm can be applied to various optimization processes.)