Description: 开发环境:Matlab
简要说明:动量-自适应学习调整算法。在实际应用中，原始的BP算法很难胜任，因此出现了很多的改进算法。BP算法的改进主要有两种途径，一种是采用启发式学习方法，另一种则是采用更有效的优化算法。本例采用动量BP算法，来实现对网络的训练过程，动量法降低了网络对于误差曲面局部细节的敏感性，有效地抑制网络陷于局部极小。-development environment : Matlab Brief Description : Momentum-adaptive learning algorithm adjustments. In practical application, the original BP algorithm competence, resulting in a lot of improved algorithm. BP algorithm improvements There are two main ways of using a heuristic approach to learning Another is the use of a more effective method of optimization. Momentum cases using the BP algorithm to achieve the network training process, Momentum for reducing error of the network for local surface details of the sensitivity, to effectively curb the network into local minima. Platform: |
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Author:zhangjian |
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Description: SCE（shuffled complex evolution ）是一种相对较新的连续性问题的元启发搜索算法。非常适合于求解具有多个局部最小的全局优化问题。SCE算法的主要特征是通过竞争进化和定期洗牌来确保每个复形获得的信息能在整个问题空间获得共享。-SCE (shuffled complex evolution) is a relatively new meta-continuity heuristic search algorithm. Very suitable for solving with multiple local minimum of the global optimization problem. SCE algorithm is characterized primarily by evolution through competition and regular cards to ensure that each complex information obtained in the whole question of access to shared space. Platform: |
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Author:胡军 |
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Description: 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 Algorithm, (transversal) Differential Evolution algorithm and Particle Swarm Optimization algorithm. Also, the GODLIKE-algorithm is included, which simply uses all of these optimizers while occasionally swapping populations between the different algorithms.
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Author:竹子的信仰 |
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Description: SFLA算法是解决组合性优化问题的算法。它是基于集合类方法的启发式研究，这种SFLA初始化于一群虚拟集合青蛙，在池塘中跳跃，搜寻最优的食物地点。青蛙们可以被看作是具有思维的的主体。一种思维可以被看作是一个思想的集合或是文化的进化。每一种思维都是由一系列策略构成。在这种策略进化期间，青蛙的思维也在发生改变，导致了他们在面向目标时方位的改变，这种思维的变化或改变的发生，正是因为青蛙受到其他更好思想的影响。-SFLA algorithm to solve portfolio optimization problems and algorithms. It is based on the collections of the heuristic research method, which is initialized to a group of SFLA virtual collection of frogs, jumping in the pond, searching for the optimal location of food. Frogs can be seen as the main body with thinking. Can be seen as a way of thinking is a set of ideological or cultural evolution. Each type of thinking is constituted by a series of strategies. Period in the evolution of this strategy, the frog is also a change of thinking, leading to goal-oriented when they change direction, this way of thinking of the change or changes occur, because frogs are better ideas. Platform: |
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Author:yangfei |
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Description: 蚁群算法是一种用来在图中寻找优化路径的机率型算法。是一种求解组合最优化问题的新型通用启发式方法，该方法具有正反馈、分布式计算和富于建设性的贪婪启发式搜索的特点。通过建立适当的数学模型，基于故障过电流的配电网故障定位变为一种非线性全局寻优问题。-Ant colony algorithm is a method used to find optimal path in the graph the probability-based algorithm. Is a combination of optimization problems to solve new general heuristic method, which has a positive feedback, distributed computing and constructive and the greedy heuristic search features. Through the establishment of an appropriate mathematical model, over-current fault-based distribution network fault location into a nonlinear global optimization problem. Platform: |
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Author:prince |
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Description: 优秀论论及对应源码。电力系统配电网的无功优化规划是保证配电网安全、经济运行的一项有效手段，是降低网损、提高电压质量的重要措施。因此，电力系统配电网无功优化规划问题的研究，既具有理论意义，又具有工程实际应用价值。配电系统最优规划问题是一个复杂的非线性组合优化问题，至今未得到很好的解决。Tabu搜索(TS—Tabu search)算法是近年来出现的用于求解组合优化问题的一种高效的启发式搜索技术。本文采用固定并联电容器作为研究对象对系统进行无功补偿，并利用智能优化方法得到使配电网损耗降低最大对应的最优节点解。并在补偿容量的邻域搜索方面做了改进，采用扩大邻域搜索范围以达到全局最优的效果。用IEEE的两个算例得出的计算结果证明了这种方法的可行性。-Excellent deals on the corresponding source code. Power system with reactive power distribution network optimal planning is to ensure the safety, economic operation of an effective means of reducing the net loss, an important measure to improve the voltage quality. Therefore, the power system reactive power optimization of distribution network planning study, not only has theoretical significance, but also has practical engineering value. Optimal distribution system planning is a complicated nonlinear optimization problem, has not been solved. Tabu Search (TS-Tabu search) algorithm is used in recent years for solving combinatorial optimization problems an efficient heuristic search techniques. In this paper, as the research object of fixed shunt capacitors for reactive power compensation system, and using intelligent optimization method to reduce the loss of the largest distribution network node corresponding to the optimal solution. Compensation capacity in the neighborhood search are Platform: |
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Author:NBB |
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Description: A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. Platform: |
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Author:soroosh |
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Description: 受帝国主义殖民竞争机制的启发，Atashpaz-Gargari和Lucas于2007年提出了一种新的智能优化算法—帝国竞争算法 (ICA)。与GA, PSO, ABC等受生物行为启发的群智能算法不同，ICA受社会行为启发，通过摸拟殖民地同化机制和帝国竞争机制而形成的一种优化方法。ICA也是一种基于群体的优化方法，其解空间由称为国家的个体组成。ICA将国家分为几个子群，称为帝国。在每个帝国内，ICA通过同化机制使非最优的国家(殖民地)向最优国家(帝国主义国家)靠近，该过程类似于PSO。帝国竞争机制是ICA的关键，ICA通过帝国竞争机制将最弱帝国中的一个或多个殖民地移动到其他帝国，使帝国之间可以进行信息交互。(Inspired by the imperialist colonial competition mechanism, Atashpaz-Gargari and Lucas proposed a new intelligent optimization algorithm, Empire competition algorithm (ICA), in 2007. With GA, PSO, ABC and other biological behavior of swarm intelligence algorithm inspired by social behavior, ICA heuristic, an optimization method is formed by simulation of colonial assimilation mechanism and competition mechanism of the empire. ICA is also a swarm based optimization approach whose solution space consists of individuals called states. ICA divides the country into several subgroups, called empires. Within each Empire, ICA moves the non optimal country (colony) to the best country (the imperialist state) through the assimilation mechanism, which is similar to PSO. Imperial competition is the key to ICA, and ICA moves one or more colonies of the weakest Empire to other empires through imperial competition, allowing the Empire to interact with each other.) Platform: |
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Author:xzfff
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Description: 路径规划是水下潜器智能控制的关键技术之一，其任务是在已知障碍物的环境中按照某一
最优指标寻找一条从起始点到目标点的无碰路径。使用蚁群算法对水下潜器三维空间路径规划问
题进行了研究，以
ACS
算法为基础设计了路径优化搜索算法，详细讨论了信息素表示方法、路径
点选取原则、启发式函数设计和信息素更新规则，给出了算法的具体流程，仿真实验结果表明，
该算法能够方便有效的实现三维空间中的路径规划。(Path planning is one of the key technologies of underwater vehicle intelligent control, whose task is to follow a certain environment in a known obstacle
The optimal index searches for a collision free path from the starting point to the target point. Three dimensional space path planning for underwater vehicle using ant colony algorithm
Questions were studied in order to
ACS
Based on the algorithm, a path optimization search algorithm is designed, and the pheromone representation method and path are discussed in detail
The principle of point selection, heuristic function design and pheromone updating rules are given. The flow chart of the algorithm is given. The simulation results show that the algorithm is very effective,
The algorithm can realize path planning in 3D space conveniently and effectively.) Platform: |
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Author:毛毛涵
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Description: 蚂蚁算法
蚁群算法是一种用来寻找优化路径的概率型算法。它由Marco Dorigo于1992年在他的博士论文中提出，其灵感来源于蚂蚁在寻找食物过程中发现路径的行为。这种算法具有分布计算、信息正反馈和启发式搜索的特征，本质上是进化算法中的一种启发式全局优化算法。蚁群系统(Ant System或Ant Colony System)是由意大利学者Dorigo、Maniezzo等人于20世纪90年代首先提出来的。他们在研究蚂蚁觅食的过程中，发现单个蚂蚁的行为比较简单，但是蚁群整体却可以体现一些智能的行为。例如蚁群可以在不同的环境下，寻找最短到达食物源的路径。这是因为蚁群内的蚂蚁可以通过某种信息机制实现信息的传递。后又经进一步研究发现，蚂蚁会在其经过的路径上释放一种可以称之为“信息素”的物质，蚁群内的蚂蚁对“信息素”具有感知能力，它们会沿着“信息素”浓度较高路径行走，而每只路过的蚂蚁都会在路上留下“信息素”，这就形成一种类似正反馈的机制，这样经过一段时间后，整个蚁群就会沿着最短路径到达食物源了。(ant algorithm
Ant colony algorithm is a probabilistic algorithm used to find the optimal path. It was proposed by Marco Dorigo in his doctoral dissertation in 1992, inspired by the way ants find paths in the search for food. This algorithm has the characteristics of distributed computation, positive feedback of information and heuristic search. It is essentially a heuristic global optimization algorithm in evolutionary algorithm. Ant colony system (Ant System or Ant Colony System) was first proposed by Italy scholars Dorigo, Maniezzo and others in 1990s. They studied ants foraging process, found that the behavior of a single ant is relatively simple, but the ant colony as a whole can reflect some intelligent behavior.) Platform: |
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Author:joyslee
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Description: 进化算法（如纯遗传算法）是元启发式算法。 这意味着，它们是一个通用框架和一组概念准则，可用于创建特定的算法以解决特定的问题。 因此，本文中介绍的示例可以看作是实验和创建进化优化代码的起点，而不是固定的静态代码库。(Evolutionary algorithms (such as pure genetic algorithms) are meta heuristic algorithms. This means that they are a generic framework and a set of conceptual guidelines that can be used to create specific algorithms to solve specific problems. Therefore, the examples presented in this article can be seen as the starting point for experiments and the creation of evolutionary optimization code, rather than a fixed static code library.) Platform: |
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Author:jjbong
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Description: A*搜寻算法俗称A星算法。A*算法是比较流行的启发式搜索算法之一，被广泛应用于路径优化领域[。它的独特之处是检查最短路径中每个可能的节点时引入了全局信息，对当前节点距终点的距离做出估计，并作为评价该节点处于最短路线上的可能性的量度。(A * search algorithm commonly known as A Star algorithm. A * algorithm is one of the more popular heuristic search algorithms and is widely used in the field of path optimization. It is unique in that it examines every possible node in the shortest path by introducing global information, estimating the distance from the end of the current node, and serving as a measure of the likelihood of the node being on the shortest path.) Platform: |
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Author:diuman |
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Description: Particle Swarm Optimization (PSO) is a newly-emerging heuristic global search algorithm based on swarm intelligence and it searches the global optimal point in the complex search space through the competition and collaboration of the particles; however, PSO is easy to get trapped in local extremum, to have premature
convergence or stagnation. In order to help PSO strike a balance between individual diversity and swarm convergence, this paper proposes an artificial immune PSO based on clonal selection. It integrates the advantages of artificial immunity and PSO and introduces the idea of immunity in PSO, namely to add immune operator in PSO so as to make PSO a new algorithm with the function of immunity. Platform: |
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Author:Dallaki |
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Description: yalmip混合整数规划优化问题，电力生产安排问题。(This file provides matlab Matlab matlab tool combined with yalmip toolbox for power system optimization of the study. MATPOWER is powerful in power flow and in solving the best power flow. It is very important for power management because it can reduce power system losses and improve system performance. In the power flow solution of the MATPOWER process, it can be applied to the convenient solution in the heuristic optimization.) Platform: |
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Author:logichui |
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Description: 基于matlab平台的启发式智能算法，萤火虫优化算法程序(Heuristic intelligent algorithm based on MATLAB platform and the program of firefly optimization algorithm) Platform: |
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Author:德米安 |
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Description: 基于万有引力搜索的元启发式优化算法，在无需其他介质的情况下，能够表现出很强的全局搜索能力。(Gravitational search meta heuristic optimization algorithm based on no other media, can show Qiangde global search ability.) Platform: |
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Author:visdo |
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Search - optimization heuristic matlab