搜索资源列表
GA
- 遗传算法求函数最值问题 matlab代码 使用轮盘赌选择 交叉 变异-Genetic algorithm for function most value problem matlab code crossover and mutation using the roulette wheel selection
yichuansuanfa
- 遗传算法求解TSP问题，采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Genetic algorithm for solving TSP problem, using the binary Gray code, based on the roulette wheel method of non-linear ranking selection, uniform crossover, mutation, but also introduce
modified_tsp
- i m trying to modified Joseph Kirk work on TSP GA here but failed miserably. Trying to modify the operators from using mutation to crossover. Then try to implement it using the map toolbox and input city coordinates, but also fail. Help me please
Electricity-
- 遗传算法的参数中，交叉概率Pc和变异概率Pm的选择是影响遗传算法行为和性能的关键所在，直接影响着算法的收敛性。-The parameters of the genetic algorithm, the crossover probability and mutation probability of Pc Pm choice is influence behavior performance of genetic algorithm and the key, the direct impact
Railway--
- 遗传算法的参数中，交叉概率Pc和变异概率Pm的选择是影响遗传算法行为和性能的关键所在，直接影响着算法的收敛性。-The parameters of the genetic algorithm, the crossover probability and mutation probability of Pc Pm choice is influence behavior performance of genetic algorithm and the key, the direct impact
Research-of-Tool-Wear-
- 遗传算法的参数中，交叉概率Pc和变异概率Pm的选择是影响遗传算法行为和性能的关键所在，直接影响着算法的收敛性。-The parameters of the genetic algorithm, the crossover probability and mutation probability of Pc Pm choice is influence behavior performance of genetic algorithm and the key, the direct impact
GA(matlab)
- 三个matlab实现的遗传算法，采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作-Three matlab genetic algorithm implemented using a binary Gray code, roulette method based on linear ranking selection, uniform crossover and mutation, but also introduces the inversi
GAProgram_matlab
- 本程序包包括遗传算法程序ga.m，突变函数mutation.m，目标函数myfun.m等。用户通过修改目标函数及算法初始参数即可用于自定义的优化问题。-This package includes the ga.m mutation genetic algorithm procedure, the function mutation.m myfun.m, objective function. The user through modifying the object function and t
GA
- 遗传算法（Genetic Algorithm，GA）是一种进化算法，其基本原理是仿效生物界中的“物竞天择、适者生存”的演化法则。遗传算法的做法是把问题参数编码为染色体，再利用迭代的方式进行选择、交叉以及变异等运算来交换种群中染色体的信息，最终生成符合优化目标的染色体。-Genetic Algorithm (Genetic Algorithm, the GA) is a kind of evolution Algorithm, the basic principle is to imitate p
0
- 具备单按键控制两级自动调光、 无限手动调光、预警闪烁（亮0.1S，灭1S循环）、低电量报警功能。 调光时具有亮度渐亮、渐暗功能，防止亮度突变的不适应。-With single-button control of two auto-dimming, Unlimited manual dimming, flashing warning (light 0.1S, 1S off cycle), low battery alarm. Dimming with brightness fa
mygReal
- The source code in C / C + + a program that implements a real-coded genetic algorithm, using any technique of crossing and mutation. The source code comments tenerv enough to do f acilmente understandable and should be included on a CD where deber a
MATLAB
- 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的，并出版了颇有影响的专著《Adaptation in Natural and Artificial Systems》，GA这个名称才逐渐为人所知，J.Holland教授所提出的GA通常为简单遗传算法（SGA）。 -In artificial intellig
GA
- fga.m为遗传算法的主程序,采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作- fga.m main program for the genetic algorithm binary Gray coding, using roulette-based non-linear ranking selection, uniform crossover and mutation operators, but also introduces t
AIS
- 免疫遗传算法matlab 程序,该算法包含抗原识别、初始抗体产生、适应度计算、向记忆细胞分化、抗体的促进和抑制、抗体产生(交叉、变异) -immune genetic algorithm Matlab procedure, the algorithm by antigen identification, initial antibody, fitness, to the memory cells, antibody for the promotion and inhibition, antibo
genetic-algorithm-based-on-matlab
- genetic algorithm based on matlab，The Genetic Algorithm (GA) is a good method to solve optimization problems. Genetic algorithms are search and optimization methods based on natural evolution. They consist of a population of bit strings transfo
PSO_PID
- 免疫粒子群算法用于PID整定。采用线性惯性系数，自适应交叉变异方法-AI-pso for PID tune.Using a linear inertial coefficient, adaptive crossover and mutation methods
jiaochapso
- 名称：带交叉因子的改进PSO算法功能：求解多维无约束优化问题特点：收敛性强，还可以加入变异算子-Name: Improved PSO algorithm with cross-factor: Solving multidimensional unconstrained optimization problem characteristics: strong convergence can also join the mutation operator
AGA
- 遗传算法中交叉和变异概率选择的自适应方法及作用机理-Genetic algorithm, crossover and mutation probability to select Adaptive Methods and Mechanism
GA
- 遗传算法源码，按照适者生存和优胜劣汰的原理，逐代（generation）演化产生出越来越好的近似解，在每一代，根据问题域中个体的适应度（fitness）大小选择（selection）个体，并借助于自然遗传学的遗传算子（genetic operators）进行组合交叉（crossover）和变异（mutation），产生出代表新的解集的种群。这个过程将导致种群像自然进化一样的后生代种群比前代更加适应于环境，末代种群中的最优个体经过解码（decoding），可以作为问题近似最优解。-Genetic
qiyixing
- 对信号的奇异性检测.检测第一类间断点matlab中的一个一维信号（freqbrk.dat）含有突变点，对其进行检测-Singularity detection of signal detection of the first class discontinuity points matlab in a one-dimensional signal (freqbrk.dat) containing the mutation point, its detection