Search - ant colony optimize

Search - ant colony optimize - List

[matlab] Clustering-algorithm-improved DL : 0: 基于蚁群算法的聚类算法以及改进的代码，实现聚类算法的优化-Clustering algorithm based on ant colony algorithm and improved code, optimize clustering algorithm
Date : Size : 6kb User :
[matlab] yiqunsuanfa DL : 0: 蚁群算法是当前研究非常火热的一种智能算法，下面的蚁群算法程序专门用于求解TSP问题，此程序由GreenSim团队于2006年初完成，最初公开发表于研学论坛，我们经过仿真检验，发现此程序的优化效率和鲁棒性都非常好。-Ant colony algorithm is currently very hot research an intelligent algorithm, the following special procedures ant colony algorithm for solving TSP problem, the program completed in early 2006 by a team GreenSim initial research study published in the forum, we have gone through simulation tests found to optimize the efficiency and robustness of this program are very good.
Date : Size : 2kb User : 刘传管
[simulation modeling] yiqunsuanfa DL : 0: 利用蚁群算法实现优化旅行商问题，一定可以运行(The use of ant colony algorithm to optimize the traveling salesman problem, will be able to run)
Date : Size : 6kb User : 文文儿
[matlab] Class_11_Code DL : 0: matlab写的蚁群算法，超级经典，不懂得可以学习学习，懂得可以研究下优化。(The ant colony algorithm written by MATLAB, super classic, does not know how to learn and learn, and knows how to optimize it.)
Date : Size : 26kb User : 韩达哒
[matlab] 蚁群bp DL : 0: 用蚁群算法优化bp神经网络，增加预测精度(Using ant colony algorithm to optimize BP neural network and increase prediction accuracy)
Date : Size : 2kb User : 浮沉yjj
[matlab] GAforPathPlaning DL : 0: 采用栅格对机器人的工作空间进行划分，再利用优化算法对机器人路径优化，是采用智能算法求最优路径的一个经典问题。目前，采用蚁群算法在栅格地图上进行路径优化取得比较好的效果，而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。利用遗传算法处理栅格地图的机器人路径规划的难点主要包括：1保证路径不间断，2保证路径不穿过障碍。用遗传算法解决优化问题时的步骤是固定的，就是种群初始化，选择，交叉，变异，适应度计算这样，那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve. The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles. The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.)
Date : Size : 5kb User : adkuhd8wy

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