搜索资源列表
Genetic_fuzzy_control
- A TSK type fuzzy controller designed by GA-by tournament.initial mutation probability
GeneticAlgorithms
- 遗传算法源代码,实现了选择操作、交叉操作和变异操作，通过适应度函数完成种群的选择及收敛.-Genetic algorithm source code, to achieve the selection operation, crossover operation and mutation operation, through the completion of the fitness function the choice of populations and convergence.
Laplace(ImageSharpening)
- 图像锐化 Laplace算子 拉普拉斯算法不检测均匀的亮度变化，而是检测变化率的变化率，相当于二阶微分。计算出的图像更加突出亮度值突变的位置。-Image Sharpening Laplace operator Laplace algorithm does not detect uniform brightness changes, but the detection rate of change of the rate of change is equivalent to second-ord
pso
- 粒子群优化(Particle Swarm Optimization - PSO) 算法是一种新兴的有潜力的进化算法( Evolutionary Algorithm - EA) .PSO 算法,和遗传算法相似,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. 但是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”(Mutation) 操作. 它通过追随当前搜索到的最优值来寻找全局最优。-pso
GAfun
- 遗传算法在函数中的应用，它包括编码、交叉、变异、选择等详细的编程，对学习遗传算法很有帮助。-Genetic Algorithms in a function application, which includes coding, crossover and mutation, select details such as programming, genetic algorithm is useful for learning.
TSP
- 提出一种改进的禁忌搜索算法来求解背包问题。该算法基于禁忌搜索技术,并采用I&D策略,同时设计了两种针对局 部最优解的变异算子。改进后的算法能有效地弥补标准禁忌算法对初始解依赖的缺陷,同时也避免了搜索停滞的现象。通过对具 体实例和随机问题的测试,表明改进后的禁忌搜索算法有更好的性能。 关-An improved tabu search algorithm to solve knapsack problem. The algorithm is based on tabu
tspmatlab
- 提出一种改进的禁忌搜索算法来求解背包问题。该算法基于禁忌搜索技术,并采用I&D策略,同时设计了两种针对局 部最优解的变异算子。改进后的算法能有效地弥补标准禁忌算法对初始解依赖的缺陷,同时也避免了搜索停滞的现象。通过对具 体实例和随机问题的测试,表明改进后的禁忌搜索算法有更好的性能。 关-An improved tabu search algorithm to solve knapsack problem. The algorithm is based on tabu
sfsf
- 提出一种改进的禁忌搜索算法来求解背包问题。该算法基于禁忌搜索技术,并采用I&D策略,同时设计了两种针对局 部最优解的变异算子。改进后的算法能有效地弥补标准禁忌算法对初始解依赖的缺陷,同时也避免了搜索停滞的现象。通过对具 体实例和随机问题的测试,表明改进后的禁忌搜索算法有更好的性能。 关-An improved tabu search algorithm to solve knapsack problem. The algorithm is based on tabu
Matlabcode
- 遗传算法，可实现多种选择和交叉、变异算法-Genetic algorithm, can realize a variety of selection and crossover and mutation algorithm
cp321123
- 这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交
GAreal_tourney
- ntroduction to Stochastic Search and Optimization, 2003 This program runs a GA with real-number coding. Elitism is used and the mutation operator is simply the addition of a Gaussian random vector to the non-elite elements. The user
pso
- This an implementation of Particle Swarm Optimization algorithm using the same syntax as the Genetic Algorithm Toolbox, with some additional options specific to PSO. Allows code-reusability when trying different population-based optimization al
GA
- 遗传算法求解函数最大值 设计的种群规模，采用的选择算子，交叉概率，变异概率，进化代数和最优解-Design of population size, using the selection operator, crossover probability, mutation probability, evolutionary algebra and the optimal solution
Genetic
- 遗传算法中，初始化，编码，解码，选择，交叉，变异，倒位的源程序-Genetic algorithms, initialization, encoding, decoding, selection, crossover, mutation, inversion of the source code
mann-kendalltubianfenxi
- mann-kendall突变点分析，vb应用程序，简单-mann-kendall mutation point analysis, vb application, a simple
Ga
- 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. -Binary Gray encoding, roulette wheel method based on non-linear ranking selection, uniform crossover and mutation operations, but also introduces the inversion operation.
genetic-algorithm-vc
- 用VC实现的遗传算法的完整工程文件。有转轮法，交叉和变异。-VC genetic algorithm implemented with the full project file. There wheel method, crossover and mutation.
360139
- In this paper, an attractive approach for teaching genetic algorithm (GA) is presented. This approach is based primarily on using MATLAB in implementing the genetic operators: crossover, mutation and selection
BGA
- 题目：非平稳时间序列突变检测的启发式分割算法（BG算法） 本源码实现了下面参考文献中的算法，并对该文献中的实例进行了仿真-Title: Non-stationary time series mutation detection heuristic segmentation algorithm (BG algorithm) of the source references to achieve the following algorithm, and examples of the liter
BMDCP
- 突变分为如下主要的几种：均值突变（最常见）、方差突变、线性回归突变（也称趋势突变）、概率突变、空间型突变、谱突变、模型参数突变，等等。贝叶斯突变检测属于概率突变检测方法，其特点是能给出突变点的概率分布图。-Mutations are divided into the following main categories: the mean mutation (the most common), variance mutation, linear regression mutation (also