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00807997
- this article can guide you to apply fuzzy ga to a model
00792863
- this article can guide you to apply fuzzy ga to a model
TSP
- 各种算法的TSP源码，包含GA、SA、TS、ANN。-TSP source of various algorithms, including GA, SA, TS, ANN.
GA
- 用遗传算法简单一元函数优化实例，效果较好，可以模仿做-Easy to use genetic algorithm function optimization examples of one dollar, the effect is better to do can be replicated
GA
- GA sources code in C-GA sources code in C++
GA
- 遗传算法，交配，进化，变异，求函数最小值-Genetic algorithm, mating, evolution, mutation, and function of the minimum
fitnessfunction
- 线性二次最优控制加权阵遗传算法优化适应度函数m文件；模糊控制器量化比例因子遗传算法优化适应度函数m文件-Linear quadratic optimal control weighted array genetic algorithm fitness function m documents quantization scale factor of fuzzy controller optimized by GA fitness function m file
matlab
- 一本关于matlab遗传算法的书, 相信对大家一定有用的。-this book is very useful for ga of matlab.
ga
- 粒子群算法与遗传算法的结合研究，值得参考！-Particle Swarm Optimization and Genetic Algorithm for the combination of research
GA
- GA遗传算法的C语言版改进实现，很适合初学者的学习-GA genetic algorithm to improve the C language version of implementation, it is suitable for beginners to learn
GA
- 遗传算法的书籍,希望对大家有所帮助-GA
(GA)
- 遗传算法的MATALAB实现，可用于模式识别或智能控制-MATALAB genetic algorithm implementation
GA
- 热能工程专业硕士研究生毕业课题：遗传算法目标函数优化-Thermal engineering graduate Master' s graduate student issues: genetic algorithm to optimize the objective function
ga
- 基于遗传算法的静态摩擦参数辨识，matlab6.5编写 -Genetic Algorithm Based on Parameter Identification of static friction, matlab6.5 prepared
GA
- 遗传算法 求解单目标问题，采用二进制编码（matlab)-using genetic algorithm to optimize Single-objective function
GA
- 遗传算法，包含选择，交叉，变异等操作，可求出Y=sin(x)在0-2π的最大值和最小值-Genetic algorithm, including selection, crossover and mutation operation, etc., can be obtained Y = sin (x) at the 0-2π Maximum and minimum
TSP_GA
- Genetic Algorithm (GA) based solver for the Traveling Salesman Problem
GA
- 遗传算法数学基础,研究遗传算法很实用的一本书。-the foundment of GA
robot_motion_planning
- This code proposes genetic algorithm (GA) to optimize the point-to-point trajectory planning for a 3-link robot arm. The objective function for the proposed GA is to minimizing traveling time and space, while not exceeding a maximum pre-define