搜索资源列表
Genetic-Algorithms
- 遗传算法的程序,其中包含编码,选择,变异,交叉,等遗传算子的实现,从而解决数学问题。- 遗传算法的程序,其中包含编码,选择,变异,交叉,等遗传算子的实现,从而解决数学问题。 Genetic algorithm program, which contains coding, selection, mutation, crossover, and other genetic operators to achieve, so as to solve mathematical problems.
MK-mlorlet
- 基于MK突变检验和morlet小波分析的降雨量预测结果,结果图-The results of rainfall prediction based on MK mutation test and Morlet wavelet analysis
Artificial-immune-optimization
- 人工免疫系统中体液免疫响应的机制优化算法,该算法模拟了抗体的产生、抗体与抗原的黏合、激励、克隆、超突变及未受激励细胞的消亡等自然过程,算法能以较快的速度完成给定范围的搜索和全局优化任务.-The mechanism of humoral immune response optimization algorithm in artificial immune system, the algorithm is simulated to produce antibody and antigen, ant
GA1
- 针对LRP车辆调度问题设计了初始种群、交叉、变异等子程序-For LRP vehicle scheduling problem to design the initial population, crossover and mutation DengZi programs
sutpend-integrate
- 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,-Using binary Gray coding, based on roulette method, non-linear ranking selection, uniform crossover, mutation,
8909421
- 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,-Using binary Gray coding, based on roulette method, non-linear ranking selection, uniform crossover, mutation,
1
- 遗传算法中的例子,对交叉概率与变异概率都进行解释-In the case of genetic algorithms, the crossover probability and the mutation probability are explained
GA
- 包括遗传算法的选择、交叉、变异子程序和主程序 ,含算例仿真(Include the selection , crossover, mutation subroutine and the main program of genetic algorithm, including examples of simulation)
mk
- mk突变检测matlab代码,以及基本说明,还请多多指教(MK mutation detects matlab code)
GA
- 简单的遗传算法实现,选择,交叉,变异,适应度函数,种群的初始化等(Simple genetic algorithm implementation, selection, crossover, mutation, fitness function, the initialization of population and so on)
genetic algorithm
- 用遗传算法求解TSP问题,包含选择,交叉,变异算子。迭代效率较高(The genetic algorithm is used to solve the TSP problem, including selection, crossover and mutation operators. The iterative efficiency is higher)
遗传算法程序
- 主要功能利用选择,交叉,变异等遗传学方法,实现最优值求解。(The main functions of selection, crossover, mutation and other genetic methods to achieve the best value solution.)
遗传算法
- 遗传算法是计算数学中用于解决最佳化的搜索算法,是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的,这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题,一定数量的候选解(称为个体)的抽象表示(称为染色体)的种群向更好的解进化。传统上,解用二进制表示(即0和1的串),但也可以用其他表示方法。进化从完全随机个体的种群开始,之后一代一代发生。在每一代中,整个种群的适应度被评价,从当前种群中随机地选择多个个体(基于它们的适应度),通过
终板 matlab程序
- 遗传算法MATLB程序,里面有遗传算法的选择、交叉、变异函数,一些简单的MABTLAB遗传算法例子!(GA MATLB procedures, there are genetic algorithm selection, crossover and mutation function, some simple examples MABTLAB GA!)
PSO算法程序
- 粒子群优化算法是一种基于群体智能的演化计算技术。与遗传算法相比,PSO没有遗传算法中的选择(Selection)、交叉(Crossover)、变异(Mutation)等操作,而是通过粒子在解空间追随最优的粒子进行搜索。(Particle Swarm Optimization (PSO) is an evolutionary computing technique based on group intelligence. Compared with the genetic algorithm, P
GA
- 遗传算法,编码采用位编码,变异交叉采用位运算,效率高(The genetic algorithm uses bit encoding, mutation crossover uses bit operation, and the efficiency is high)
粒子群优化研究工具箱
- 粒子群优化研究工具箱是为了协助解决粒子群优化(PSO)过早收敛问题的论文研究。(Gbest PSO, Lbest PSO, RegPSO, GCPSO, MPSO, OPSO, Cauchy mutation, and hybrid combinations)
遗传算法求解VRP问题的技术报告
- 本文通过遗传算法解决基本的无时限车辆调度问题。采用车辆和客户对应排列编码的遗传算法,通过种群初始化,选择,交叉,变异等操作最终得到车辆配送的最短路径。通过MATLAB仿真结果可知,通过遗传算法配送的路径为61.5000km,比随机配送路径67km缩短了5.5km。此结果表明遗传算法可以有效的求解VRP问题。(In this paper, genetic algorithm is used to solve the basic vehicle scheduling problem without
_基于交叉库与并行变异的自适应遗传算法_苗振华
- 遗传算法在交叉,变异中的并行关系。。。。。。。。。(Parallel relation of genetic algorithm in crossover and mutation)
差分进化算法
- 一个增强版的遗传算法,用于波束赋形,可供初学者学习使用(Parallel relation of genetic algorithm in crossover and mutation)