Description: 利用C++编写蚁群优化算法解决51城市旅行商问题-prepared Ant Colony Optimization Algorithm for 51 city Traveling Salesman Problem Platform: |
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Description: 是一个基于Matlab软件的模糊C-means聚类算法原代码-Matlab is a software based on the fuzzy C-means clustering algorithm source code Platform: |
Size: 2048 |
Author:杨明 |
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Description: This a demo program of image edge detection using ant colony, based on
the paper, "An Ant Colony Optimization Algorithm For Image Edge Detection," 基于蚁群算法的图像边缘检测。IEEE于2008收录的文章.有matlab源程序和“An Ant Colony Optimization Algorithm For Image Edge Detection”这篇PDF文章。希望对大家有一定帮助。-This is a demo program of image edge detection using ant colony, based on the paper, " An Ant Colony Optimization Algorithm For Image Edge Detection," Based on Ant Colony Optimization Image Edge Detection. IEEE in 2008 included in the article. Matlab source code and there is " An Ant Colony Optimization Algorithm For Image Edge Detection" This PDF article. Hope to assist everyone must have. Platform: |
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Author:miaosiyi |
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Description: 无约束连续函数优化的人工蚁群算法通用MATLAB源码
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
-Unconstrained optimization of continuous function of artificial ant colony algorithm for general-purpose MATLAB source code。
This source code is an implementation of artificial ant colony algorithm for unconstrained optimization of continuous function to solve for the case containing the constraints, you can first use the penalty function and other methods to deal with the problem into the unconstrained model, then use the origin codes solving Platform: |
Size: 2048 |
Author:孙准 |
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Description: 蚁群算法源代码，无须修改便可以直接编译执行-Ant colony algorithm source code, no need to change the implementation can be directly translated Platform: |
Size: 178176 |
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Description: 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 optimization of continuous function to solve for the case containing the constraints, you can first use the penalty function and other methods to deal with the problem into a non-binding model, and then use the source code is solved, Platform: |
Size: 2048 |
Author:张望 |
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Description: 基于蚁群算法的PID控制参数优化Matlab源码-PID Control Based on Ant Colony Optimization Algorithm for Matlab source Platform: |
Size: 5120 |
Author:天道酬勤 |
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Description: 基于蚁群算法的PID控制参数优化Matlab源码,步骤详细，附有说明。-PID Control Based on Ant Colony Optimization Algorithm for Matlab source, the steps in detail, with explanation. Platform: |
Size: 2048 |
Author:程玉昆 |
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Description: 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 using the penalty function and other methods to deal with the problem into the unconstrained model, then use the source code solved. Platform: |
Size: 12288 |
Author:ly |
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Description: 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 Platform: |
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Author:liuyu |
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Description: colony optimization, It is a
population based approach that uses the exploration of positive feedback as well as
greedy search. The proposed method was inspired natural behavior of the ant
colonies on how they find the food source and bring them back to their nest by
building the unique trail formation.-colony optimization, It is a
population based approach that uses the exploration of positive feedback as well as
greedy search. The proposed method was inspired natural behavior of the ant
colonies on how they find the food source and bring them back to their nest by
building the unique trail formation. Platform: |
Size: 20480 |
Author:Izaque Souza |
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Description: In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.
This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants. From a broader perspective, ACO performs a model-based search and share some similarities with Estimation of Distribution Algorithm. Platform: |
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Author:reyhooon
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Search - Ant colony optimization source