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GA.rar
- 一个动态遗传算法代码 matlab的,采用全方位的两点杂交、两点变异的改进的加速遗传算法（IAGA）,A dynamic genetic algorithm matlab code, the use of comprehensive two hybrid, two variations of improved accelerating genetic algorithm (IAGA)
GA
- GA.dll是封装遗传算法的动态连接库，内部潮流计算使用的是PQ方法，该潮流计算方法已封装在该DLL内。如果需要采用其他的潮流计算方法，需要重新来设计DLL的接口函数及更改遗传算法中目标函数的计算方法。-GA.dll genetic algorithm is encapsulated dynamic link library, the internal flow calculation using the PQ method, the power flow calculation method
A_real-time_adaptive_PID_controller_step_motor
- 传统PID控制器通常难以满足多变量、非线性、强耦合的步进电机动态响应和精 确调速要求,结合传统PID控制和模糊控制及遗传算法(GA)整定PID参数的优点,设计基于 模糊遗传算法的实时自适应步进电动机PID控制器,充分发挥传统和智能控制策略各自的优 势。仿真结果表明,该实时自适应步进电动机PID控制器,具有很好的自适应能力和抗负载扰 动能力。在稳定性、动态速度响应诸方面均优于传统的PID控制器和模糊控制器,系统达到了 较高调速性能和控制精度。 -Traditional PI
insulargenetica-win32-qt4.5-1.18beta
- 这是并行遗传算法的实现与“环”狭隘的拓扑结构。算法在进化提供了一个动态的遗传算子的选择。该库支持的26个遗传算子。这是跨平台的遗传算法用C+ +编写的。-This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library
GA_for_clustering
- Genetic algorithms (GAs) have recently been accepted as powerful approaches to solving optimization problems. It is also well-accepted that building block construction (schemata formation and conservation) has a positive influence on GA behavior.
cppfrance_ALGORITHME-GENETIQUE-RCPSP___Page
- dynamic developing for the TSP with GA
genetic-algorithm
- 用基本遗传算法求解一维无约束优化问题 用顺序选择遗传算法求解一维无约束优化问题 用动态线性标定适应值的遗传算法求解一维无约束优化问题 用大变异遗传算法求解一维无约束优化问题 用自适应遗传算法求解一维无约束优化问题 用双切点遗传优化求解一维无约束优化问题 用多变异位自适应遗传优化求解一维无约束优化问题 -The basic genetic algorithm with one-dimensional sequence of unconstrained optimizat
GA
- 遗传算法的mATLAB实现 动态搜索 经典成像-Genetic Algorithm mATLAB dynamic search
GA-pareto
- 遗传算法的多目标优化算例，动态显示优化过程pareto前端的分布情况。-Genetic algorithm is a multi-objective optimization example, dynamic display of pareto optimal process the distribution of the front end
Expressing-of-Hybrid-BFA-PSO-BFA-GA-Algorithms-an
- Expressing of Hybrid BFA-PSO,BFA-GA Algorithms and Dynamic-environment & Cooperative BFA. ------------------------------------------------ this file is with format of "SWF" and presented by "prof . Ji Zhen" . number of pages: 60 . including
GA_opt
- Optimization of Genetic algorithm (GA) parameters through new dynamic approach.Hope this code will great helpful for beginners.
GA-TSP
- 经典的基于GA遗传算法的路径规划问题的实现，能动态的实现所需功能，值得学习研究-The path planning problem of GA based on genetic algorithm classic, can realize the dynamic functions are required, it is worth learning research
FA2
- 一种改进的萤火虫算法解决动态0-1背包问题。经过测试，算法就有良好的性能。-Firefly Algorithm (FA), Genetic Algorithm (GA) and Differential Evolution (DE) have been widely used for static optimization problems, but the applications of those algorithms in dynamic environments are rela
Static_dynamic_Geography_GA
- Static & Dynamic environment Biogeography base algorithm with DE and GA
using-GA-in-antenna-array
- 提出了整数编码，动态调整交叉概率、变异概率，并将适应度函数设为最大相对旁瓣电平,一种改进遗传算法的优化方法来实现直线稀疏阵列的设计-Proposed integer coding, dynamic adjustment of crossover probability, mutation probability, and the fitness function is set to the maximum relative sidelobe level, an improved genetic
Hybrid-GA-PSO-Code
- DOUBLE FOUR-BAR CRANK-SLIDER MECHANISM DYNAMIC BALANCING BY Hybrid GA PSO ALGORITHMS-DOUBLE FOUR-BAR CRANK-SLIDER MECHANISM DYNAMIC BALANCING BY Hybrid GA PSO ALGORITHMS
QGA11
- 量子遗传算法（QGA-Quantum Genetic Algorithm）是量子计算与经典遗传算法(GA)相结合而产生的一个新的研究领域。算法利用了量子计算的量子并行、量子纠缠特性，采用了多状态基因量子比特编码方式和量子旋转门更新操作，引入动态和静态调整旋转角机制和量子变异，使得算法比经典遗传算法具有更强的并行处理能力、更快的收敛速度且比传统信号检测算法具有更高的效率。-Quantum Genetic Algorithm (QGA-Quantum Genetic Algorithm) is
GA(PSO)
- 经典的遗传算法的实现，因为是框架因此可以直接套用，交叉概率、变异概率可以设成动态的-The realization of the classical genetic algorithm, because it is the framework can be directly applied, the probability of crossover probability, mutation probability can be set into a dynamic
GA
- 利用GA遗传算法进行动态路径规划，完成最优轨迹的生成，适合新手入门学习。(Using GA genetic algorithm for dynamic path planning, the completion of the optimal trajectory generation, suitable for beginners to learn.)
基于遗传算法的小波神经网络在股票预测中的应用
- 动态粒子算法，适合适合科研人员和学生进行优化和调参。新手理解鱼群算法，希望大家可以认真学习其中的道理。(Dynamic particle algorithm is suitable for scientific researchers and students to optimize and participate. Novice understands Fish Swarm Algorithms, I hope you can seriously learn the truth.)