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蚁群算法的Matlab程序，用于连续函数优化-Ant colony algorithm Matlab program for continuous function optimization
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此源码是对人工蚁群算法的一种实现，用于无约束连续函数的优化求解，对于含有约束的情况，可以先使用罚函数等方法，把问题处理成无约束的模型，再使用本源码进行求解。-This source code is an implementation of artificial ant colony algorithm for unconstrained continuous function optimization, with constraints for the case, you can start u
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蚁群算法源码,蚁群算法简介+算法实现代码，基于C-Ant colony algorithm source code, ant colony optimization algorithm About+ code, based on C++
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This MATLAB implementation computes a correspondence between two shapes
based on ant colony optimization (ACO). The input shapes can be either
two 2D contours (open or closed) or two arbitrary sets of 2D points. The
algorithm is described in de
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其中包含了三种算法，粒子群优化方法，遗传算法和蚁群算法-Which contains the three algorithms, particle swarm optimization, genetic algorithms and ant colony algorithm
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A fault identification with fuzzy C-Mean clustering
algorithm based on improved ant colony algorithm (ACA) is
presented to avoid local optimization in iterative process of
fuzzy C-Mean (FCM) clustering algorithm and the difficulty in
fault cl
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目前，物联网备受关注。在多网关无线传感网络与物联网的异构融合中，通过网关连接是最常用的策略。本程序利用基于蚁群优化的算法，寻找每个节点至网关的最优路径。-Recently, the Internet of Things is getting more and more attention.There are different approaches to integrate WSN into the Internet. The most usual one is to connect the W
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蚁群算法(ant colony optimization, ACO)，又称蚂蚁算法，是一种用来在图中寻找优化路径的机率型算法。-ACO (ant colony optimization, ACO), also known as ant algorithm is a method used to find the optimal path in the graph the probability-based algorithm.
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基于蚁群算法的PID控制参数优化Matlab源码-PID control algorithm based on ant colony parameter optimization Matlab source
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用蚁群算法来解决tsp问题，效率较高，可以得到全局最优解-Tsp with ant colony algorithm to solve the problem, more efficient, you can get the global optimal solution
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这是一个使用蚁群算法解决旅行商问题（TSP）的一个解法，算法清晰易懂。-This is a solution of an ant colony algorithm to solve the traveling salesman problem (TSP), the algorithm is clear and easy to understand.
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matlab编写的蚁群算法，即在图中寻找优化路径的机率型算法，结合遗传算法进行了改进。-ant colony algorithm matlab prepared in the graph to find the probability-based algorithm for optimal path, combined with genetic algorithm is improved.
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基于多目标优化问题的改进蚁群算法的设计描述-Improved Ant Colony Algorithm design descr iption based on the multi-objective optimization problem
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蚁群算法是近年来提出的一种基于种群寻优的启发式搜索算法。该算法受到自然界中真是蚁群通过个体间的信息传递，搜索。-The ant colony algorithm is proposed in recent years a heuristic search algorithm optimization based on population. The algorithm is by nature really ant colony to pass information between indiv
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蚁群算法优化计算。多个路径中选择最优路径，来确定最优计算顺序-Ant colony optimization algorithm. Multiple paths, select the optimal path to determine the optimal calculation sequence
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蚁群算法旨在用反复迭代的方法找到目标问题的最优解，通过建立信息素信息对解空间进行的搜索来实现。本程序应用蚁群优化算法进行图像的边缘检测。-The ant colony algorithm is designed with iterative method to find the optimal solution of the target problem, the search of the solution space through the establishment of pheromon
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连续优化问题如(Schaffer函数)的蚁群算法源码和图像-Continuous optimization problems such as (Schaffer the function) ant colony algorithm source code and images
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TSP问题蚁群算法,是一种用来在图中寻找优化路径的机率型算法。-The TSP problem ant colony algorithm is used to find the probability of the optimal path algorithm in the figure.
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：在介绍基本蚁群算法原理的基础上，对其作了许多改进以提高其全局优化寻优速度，并给出了
详尽的新算法编程仿真实现步骤，最后将未改进的基本蚁群算法与本文改进后的蚁群算法分别应用于TSPLIB中的Att532 P问题进行了仿真实验-Abstract：Firstly．the principle of basic ant colony algorithm (ACA)is introduced．Then．a series of schemes
to improve the global optimi
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遗传算法优化B P神经网络的目的是通过遗传算法得到更好的网络初始权值和阈值, 其
基本思想就是用个体代表网络的初始权值和阈值、 个体值初始化的B P神经网络的预测误差作为该个体的适应度值, 通过选择、 交叉、 变异操作寻找最优个体, 即最优的B P神经网络初始权值。除了遗传算法之外, 还可以采用粒子群算法、 蚁群算法等优化B P神经网络初始权值。-Genetic algorithm to optimize BP neural network is designed by means of g
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