搜索资源列表
遗传算法解TSP
- 实现用固定变异概率和自适应变异概率解tsp问题的比较，自适应式算法采用基于种群差异度的自适应算法，详见实验报告-achieve fixed mutation probability and Adaptive Solutions tsp mutation probability of comparison, Adaptive Algorithm-based differences in the populations adaptive algorithm, as detailed experime
matlog
- 物流分析工具包。Facility location: Continuous minisum facility location, alternate location-allocation (ALA) procedure, discrete uncapacitated facility location Vehicle routing: VRP, VRP with time windows, traveling salesman problem (TSP) Networks: Sho
cs2ct
- 在页面中实时转换简繁体，使您的网站适合所有的人群。-pages in real-time conversion Brief History, your site is suitable for all populations.
遗传算法实现旅行商问题
- 本算法中采取了种群规模为100，同时采用轮盘赌来获取种群。开始使用随机的方法得到初始的种群-the algorithm adopted a population size of 100, using roulette to access populations. Using the stochastic method initial Stocks
AGA.rar
- 采用了保优的选择遗传算法 终止条件的判断是：到达一定的代数。可改进为：相邻若干代的种群平均适应值的变化来判断。若相邻若干代的种群平均适应值为变化或者是变化小于某一阈值，表示算法已经收敛，则退出算法。 选择算子：轮盘赌选择； 交叉算子：单点交叉,随机选择计算此适应度值，若大于当前最佳适应度值则降低交叉概率，否则不变； 变异算子：模板,对于优势个体，除采用低概率变异外，变异位置应采取权值越大，变异概率越小的原则,而对劣势个体则相反.,Paul used the choice of excel
zuixiaofugai
- 首次提出利用PSO跟踪动态系统 文献[ 36 ]提出用自适应PSO来自动跟踪动态系统的变化,该方法通过对种群中最好微粒的检测和对微粒重新初始化, 有效增强了PSO对系统变化的跟踪能力-PSO is first used to track the dynamic system literature [36] proposed adaptive PSO with dynamic system to automatically track changes in populations by the
Vicsek
- Vicsek模型的仿真代码 可以用作大规模人群的行为研究-The Vicsek model simulation code can be used as the behavior of large populations
Cmonihuaduojinhua
- 实现了一个简单的花朵进化的模拟过程。 花朵的种群数量是10，共进化了50代。 -The realization of a simple simulation of the evolution of flowers. Flower populations is 10, a total of 50 on behalf of evolution.
penna_dead
- PEnna生物模型中的死亡和繁殖规律，运用此规律可以模拟生物种群的数量。-Penna biological model of death and reproduction of the law, the application of this law can simulate the number of biological populations.
Optimizers
- 一系列好用的用户友好的启发式优化算法，包括非自适应算法，基于模拟退火算法的种群算法，基本遗传算法，差分进化算法以及粒子群优化算法。此外，也包括神圣算法，它利用了所有这些优化算子，虽然有时交换种群之间的不同算法。-A nice set of user-friendly heuristic optimizers. Included are a non-adaptive, population based Simulated Annealing algorithm, a basic Genetic A
M_GA
- 用4个种群来优化函数，每次取三个种群里面的最佳放入第四种群，经过反复迭代后取得函数的最佳值-4 used to optimize the function of populations, each from three of the best stocks inside Add the fourth population, after repeated iterations of the optimal value function
gui_antminer1.2.1
- Short descr iption: GUI Ant-Miner is a tool for extracting classification rules from data. It is an updated version of a data mining algorithm called Ant-Miner (Ant Colony-based Data Miner), which was proposed in 2002 by Parpinelli, Lopes and Freitas
MakeDensityBasedClusterer.java.tar
- 基于局部搜索能力强、收敛速度快的特点,首先初始化一个没有子种群的全局种群,再在全局种群中采用迭代搜索,并对其中的个体进行聚类,当聚类簇中的个体数目达到规定的最小规模时形成一个子种群,然后在各子种群中进行迭代搜索并重新进行聚类,从而提高进化过程中种群的多样性,增强算法跳出局部最优的能力.该算法基于weka，用于weka拓展功能，需要 weka算法包支持。-Based on the local search ability, the characteristics of fast convergen
voterra
- 利用三种方法解决Volterra的两个种群的生态学问题。-Volterra use three methods to solve the problem of two populations of Ecology.
grobots20080820
- GROBOT类似于robocode的编程机器人，然后在虚拟环境里竞赛的东东，这个东西模拟生物种群的行为，非常的有意思，强烈建议下载-GROBOT similar robocode programming robots, and then race in a virtual environment Dongdong, this thing simulate the behavior of biological populations, very interesting, it is strongl
SystematicsandConservationofInsectDiversity
- Systematics is the study of the relationships between groups of any size, including species and populations-Systematics is the study of the relationships between groups of any size, including species and populations
fd_predator_prey
- 采用有限元的方法求解计算捕捉问题predator-prey -program which applies the finite difference method to estimate solutions of a pair of ordinary differential equations that model the behavior of a pair of predator and prey populations.
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.
genetic_algorithm
- 遗传算法入门实例一：PID参数的优化[v1.0] 本文件夹包含： 图片IMG_0084 和IMG_0086为实验照片 IMG_0084为初始种群中某个体的PID调整效果 IMG_0086为进化了N(到底多少代我也没有去数)代之后的PID调整效果 文件GA为正文 源码\GA\ 为实验代码，WINAVR20060421+AVR Studio 4.12-Introduction example of a genetic algorithm: PID parameters optim
Chaotic-populations-in-genetic-algorithms
- Chaotic populations in genetic algorithms