搜索资源列表
GA
- 十进制、二进制遗传算法以及混合遗传算法matlab源代码(Matlab Code for Genetic Algorithm in Bin and Dec format and Mix Genetic Algorithm with an example. 17 files include functions for mutation, hybird, fitness and so on.)
GA-BP
- 算法基本要素: 1.染色体编码方法 2.适应度函数 3.遗传操作—-(选择、交叉、变异) 4.运行参数—(参数:群体大小M、遗传代数G、交叉概率Pc和变异概率Pm)(Basic elements of algorithm: 1. chromosome coding method 2. fitness function 3. - the genetic operation (selection, crossover and mutation) 4. operating pa
gatbx1.3
- matlab的遗传算法工具箱,包含选择、交叉、变异等算子(Matlab genetic algorithm toolbox.Operators such as selection, crossover and mutation are included.)
EvolutionaryNutrition
- Genetic code for modelling evolution and nutrition
遗传算法程序 matlab
- 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(As the main program of genetic algorithm, binary Gray encoding is adopted, nonlinear ranking selection based on roulette method, uniform crossover, mutation operation, and inversion operat
liziqun
- 粒子群算法,也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization),缩写为 PSO, 是近年来由J. Kennedy和R. C. Eberhart等 开发的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的"交叉"(Crossover) 和"
GA
- 使用python实现遗传算法的基本功能,包括变异,交叉,选择(Using Python to achieve the basic functions of genetic algorithms, including mutation, crossover, selection)
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。(Genetic algorithm is a search algorithm used to solve the optimization in computational mathematics. It is one of the evolutionary algorithms. Evolu
Mann-Kendall突变检测
- matlab,Mann-Kendall突变检测 ,数据序列(MK mutation detection)
GA
- In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate h
人工免疫算法源程序
- 人工免疫算法通过复制、交叉、变异主要完成对象的建模、优化和预测。(The artificial immune algorithm completes the modeling, optimization and prediction of the object by replicating, crossover and mutation.)
MMK
- M-K突变检验,进行趋势分析和突变点检验(M-K mutation test, trend analysis and mutation point test)
MK趋势与突变检验
- 这是Man-kandell趋势突变检验,可用于时间序列的趋势与突变点的检测(man-kandell trend test and mutation plot)
ACATSP
- 改进的人工蚁群算法引入遗传变异算子的MATLAB实现(MATLAB implementation of improved artificial ant colony algorithm introducing genetic mutation operator)
pso
- 用于优化参数,粒子群算法,也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization),缩写为 PSO, 是近年来由J. Kennedy和R. C. Eberhart等[1] 开发的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它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”
Untitled
- 用于数据处理,检测数据的变化趋势和突变点(Used for data processing, changing trends and mutation points of data)
Genetic1
- 遗传算法,改进了交叉过程,初始过程以及变异过程,使结果更加精确(Genetic Algorithm, the process of cross-process, initial process and mutation is improved to make the result more accurate.)
TSP-PSO
- 混合粒子群算法摒弃了传统粒子群算法中的通过跟踪极值来更新粒子位置的方法,而是引入了遗传算法中的交叉和变异操作,通过粒子同个体极值和群体极值的交叉以及粒子自身变异的方式来搜索最优解。(Hybrid particle swarm algorithm instead of the traditional particle swarm algorithm in the method to update the position of the particle by tracking the maximu
c1遗传算法
- 根据遗传变异的生物规律改变出的遗传变异算法(Genetic mutation algorithm based on biological laws of genetic variation)
S-C-M
- 此文件包含了遗传算法的选择 selection,交叉 cross 和变异mutation 三个文件(this file consists of three programs which are selection. cross and mutation of the genetic algorithm.)