Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似,是一种基于叠代的优化工具。系统初始化为一组随机解,通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较,PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化,神经网络训练,模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross - (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications Platform: |
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Author:张正 |
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Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似,是一种基于叠代的优化工具。系统初始化为一组随机解,通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较,PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化,神经网络训练,模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications Platform: |
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Author: |
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Description: pso算法的代码,是一种基于叠代的优化工具。系统初始化为一组随机解,通过叠代搜寻最优值,-PSO algorithm code is based on an iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values, Platform: |
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Author:张林 |
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Description: matlab仿真模拟退火算法的简单搜索过程,随机数用数组实现-Matlab simulation annealing simple search process, with a few random arrays to achieve Platform: |
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Author:zhang yg |
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Description: % COMPDIR Computes a search direction in a subspace defined by Z.
% Helper function for NLCONST.
% Returns Newton direction if possible.
% Returns random direction if gradient is small.
% Otherwise, returns steepest descent direction.
% If the steepest descent direction is small it computes a negative
% curvature direction based on the most negative eigenvalue.
% For singular matrices, returns steepest descent even if small.- COMPDIR Computes a search direction in a subspace defined by Z. Helper function for NLCONST. Returns Newton direction if possible. Returns random direction if gradient is small. Otherwise, returns steepest descent direction. If the steepest descent direction is small it computes a negative curvature direction based on the most negative eigenvalue. For singular matrices, returns steepest descent even if small. Platform: |
Size: 1024 |
Author:张风 |
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Description: 深度优先搜索算法Matlab源码
% 此程序从国外网站收集得到,是标准的深度优先搜索算法,可实现节点遍历和检测回路的功能,详细情况请看原英文注释
% 我在此程序中添加了随机性,即遇到分叉时,随机选下一个节点,成为随机深度优先搜索算法-Depth-first search algorithm Matlab source this procedure site collected from abroad, is the standard depth-first search algorithm, can be achieved and the detection circuit node traversal functions, details see the original English Notes I added this procedure randomness, that is, bifurcation encountered when a randomly selected node, become a random depth-first search algorithm Platform: |
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Author:tangjia |
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Description: 对电力系统57接点应用随机搜索法进行潮流分析,及电压稳定分析-Contact 57 on the power system using random search method for trend analysis, and voltage stability analysis Platform: |
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Author:jiangzhiling |
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Description: < MATLAB遗传算法工具箱及应用>>介绍了如何在MATLAB中完成遗传算法的应用。遗传算法[Genetic Arithmatic,简称GA]是以自然选择和遗传理论为基础,将生物进化过程中适者生存规则与群体内部染色体的随机信息交换机制相结合的高效全局寻优搜索算法。GA摒弃传统的搜索方式,模拟自然界生物进化过程,采用人工进化的方式对目标空间进行随机优化搜索。MATLAB是MATHWORKS公司的一套高性能的数值计算和可视化软件。MATLAB遗传算法工具箱及应用
-Genetic Algorithm [Genetic Arithmatic, referred to as GA] is based on natural selection and genetic theory, the process of biological evolution survival of the fittest rules and groups of chromosomes within the clearing-house mechanism of the random combination of efficient global optimization search algorithm. GA to abandon the traditional search methods to simulate the process of natural biological evolution, artificial evolution approach on the target stochastic optimization search space. Mathworks Inc. MATLAB is a high-performance numerical computation and visualization software. MATLAB genetic algorithm toolbox and its application Platform: |
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Author:吴晓晖 |
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Description: 针对多椭圆检测问题提出了一种快速随机检测算法。该算法利用在图像中随机采样到的一个边缘点和
局部搜索到的两个边缘点以及这三个点的邻域信息确定候选椭圆,再将候选椭圆变换为对应圆,通过确认真圆来确
认真椭圆。在确定候选椭圆时,最大限度地减少随机采样点数 剔除更多的非椭圆点,降低了无效采样,减少了无效
计算。数值实验结果表明:该算法具有良好的鲁棒性,其检测速度比同类算法快-Ellipse detection problem for many a fast random detection algorithm. The algorithm uses random sampling in the image of an edge point and the local search to the two edge points, as well as the three-point neighborhood information to determine the candidate ellipse, and then transformed into the corresponding elliptical candidate won, through the identification of real yen to confirm really elliptical. In determining when a candidate ellipse, to minimize random sampling points ‰ remove more non-oval points, reducing invalid sampling, to reduce the calculation invalid. Numerical experimental results show that: the algorithm has good robustness, and its detection faster than similar algorithms quickly Platform: |
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Author:刘镖峰 |
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Description: 此程序从国外网站收集得到,是标准的深度优先搜索算法,可实现节点遍历和检测回路的功能,详细情况请看原英文注释
我在此程序中添加了随机性,即遇到分叉时,随机选下一个节点,成为随机深度优先搜索算法-This procedure has been collected from the foreign website, the standard depth-first search algorithm, can be achieved and the detection circuit node traversal functions, see the original details of the Note English I would like to add a random process, that is encountered in bifurcation when a randomly selected node, as a random depth-first search algorithm Platform: |
Size: 6567936 |
Author:fly |
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Description: 标准的深度优先搜索算法,可实现节点遍历、产生随机路由、检测图中是否有回路等功能,-Standard depth-first search algorithm, the node traversal can be achieved, resulting in a random routing, testing whether there is any loop diagram functions Platform: |
Size: 2048 |
Author:quzhijian |
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Description: 本文将排课五要素绑定、封装成课元、课栈两个向量,并以二维权值矩阵描述课元
和课栈之间的关联系。
提出了最佳匹配和遗传算法的排课算法,以随机生成的二维数字矩阵来反映课元和
课栈的关联权重,对数字矩阵组处理和最佳匹配得到的匹配偶图组为遗传算法的初始种
群,以排课各种原则的加权和为目标函数,在遗传算子控制下迭代来寻求更优的匹配结
果即使目标函数最小的偶图匹配结构,进而得到满意的排课结果。
提出了关联匹配和禁忌搜索的排课算法,以随机二维数字矩阵描述课元和课栈之问
的关联权重,按照重权优先并根据正确性原则进行约简,获得课元和课栈之间的匹配偶
图。在此基础上,引入禁忌搜索算法,以排课的完备性原则、合理性原则和人性化原则
的加权和为目标函数,以随机二维权值矩阵生成的匹配偶图为初始解,对二维权值矩阵
进行扰动构成搜索邻域,以生成的匹配偶图为禁忌对象,采用全局藐视准则,获得最优
的排课方案。
以Matlab为平台,利用Excd数据库和Mallab的互联实现数据交换,编写了两套
算法的应用程序,通过实例来验证两套排课算法,结果表明两套算法是可行的。-Arranging the five elements of this paper, binding, packaging into a class element, class stack of two vectors and matrices described by two classes per Rights
And the relationship between class stack link.
Offers the best match and Genetic Algorithm Platoon algorithm to randomly generated two-dimensional figures to reflect the class element and matrix
Class stack associated with weight, the digital matrix group received treatment and the best matching group bipartite graph matching the initial kind of genetic algorithm
Group to the weighted course arrangement of principles and the objective function, under the control of the genetic operator iteration to seek the better match Results
Results even if the objective function structure of the smallest bipartite graph matching, and then Timetabling satisfactory results.
Match the proposed association Timetabling algorithm and tabu search, a random two-dimensional digital matrix element and the class description class stack of Q Platform: |
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Author:张林杰 |
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Description: 这个程序主要是用来设计实现一个蒙特卡洛的算法 采用matlab设计 可以应用在随机搜索方面-This program is mainly used to design and implement a Monte Carlo algorithm using matlab design can be applied to random search and Platform: |
Size: 1024 |
Author:肥肥 |
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Description: PSO 算法属于进化算法的一种,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 algorithm is an evolutionary algorithm, and genetic algorithm is similar, it is starting from a random solution, by iteration to find the optimal solution, it is also to evaluate the fitness of the solution by the quality, but it is much simpler than the rules of the genetic algorithm, It is not genetic algorithms " cross" (Crossover) and " variant" (Mutation) operations, which by following the optimal value of the current search to find the global optimum Platform: |
Size: 20480 |
Author:shitou |
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Description: 用matlab实现的rrt快速随机搜索树算法,方便易于理解。(Using MATLAB to achieve the RRT fast random search tree algorithm, convenient and easy to understand.) Platform: |
Size: 2611200 |
Author:又四日
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Description: 免疫算法是受生物免疫系统的启发而推出的一种新型的智能搜索算法,是一种确定性和随机性选择相结合并具有"勘探"与"开采"能力的启发式随机搜索算法。
算法主要的步骤:
(1)抗原识别与初始抗体产生。
(2)抗体评价
(3)免疫操作
免疫算法的特点:
(1)全局搜索能力
(2)多样性保持机制
(3)鲁棒性强
(4)并行分布式搜索机制(A new intelligent immune algorithm is inspired by the biological immune system and the introduction of the search algorithm is a deterministic and random selection are combined with "heuristic random search algorithm exploration" and "Exploitation" ability.
Main steps of the algorithm:
(1) antigen recognition and initial antibody production.
(2) antibody evaluation
(3) immunization
Characteristics of immune algorithm:
(1) global search capability
(2) diversity retention mechanism
(3) robust
(4) parallel distributed search mechanism) Platform: |
Size: 27648 |
Author:傲视天下
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Description: 使用随机搜索方法,进行局部最优求解,matlab语言版本。(The random search method is used to perform local optimal search.) Platform: |
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Author:tdcqren |
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