搜索资源列表
PSO-image-segmentation-algorithm
- 为了提高算法的执行效率, 应用粒子群算法求取图像中任意两点间最短路径来定位目标边界, 并与经典的基于Dijkstra 动态规划图搜索的Liv e Wire 算法进行比较.-In order to improve the efficiency of the algorithm, particle swarm algorithm to strike any of images to locate the shortest path between two object boundaries, and
DVHOP2
- 基于粒子群的DV_hop算法的运用，有很好的效果，定位比较好-Algorithm based on particle swarm DV_hop use, have a good effect, better positioning
DVHOPS
- 基于粒子群和基于PSO和基于遗传算法的DV-hop算法的定位，有比较好的效果-Particle swarm based PSO, based on genetic algorithm DV-hop positioning algorithm, a relatively good results
Desktop
- 基于粒子群的定位系统理论，有很强的理论推导公式，希望对你有用-Positioning system based on particle swarm theory, there is strong theoretical derivation of the formula, you want to be useful
PSOBC-dvhop
- 基于改进的粒子群算法的一个网络节点定位算法，并和传统的DVhop方法做了比较。-Based on the improved particle swarm algorithm of a network node localization algorithm, and the method and traditional DVhop were compared.
4
- 基于粒子群的处理算法，有很好的定位计算结果，处理效果很好的，-Particle swarm algorithm based on the processing, have very good positioning the calculation results, the treatment effect is very good.
Sensor-network
- 传感器网络的粒子群优化定位算法，有多篇经典文献，并有仿真实例。-Sensor network of particle swarm optimization localization algorithm, have more than paper classical literature, and a simulation example.
the-simulation-examples
- 基于差分进化和粒子群优化算法的混合优化算法，基于差分进化算法的定位算法，及其仿真。-Based on differential evolution and the particle swarm optimization algorithm hybrid optimization algorithm, evolutionary algorithm based on difference of localization algorithm, and its simulation.
the-simulation-and-examples
- 传感器网络的粒子群优化定位算法，及其基于差分进化算法的定位算法，带有2个simulink仿真。-Sensor network of particle swarm optimization localization algorithm, and its evolution algorithm based on difference of localization algorithm, with two simulink.
pso_bc
- 基于细菌子粒子群的无限传感器网络的定位算法 可供大家参考-Based on the infinite positioning of the sensor network in the bacterial sub-particle swarm algorithm available reference
d4ef13.ZIP
- 基于粒子群优化的改进加权质心定位算法Particle swarm optimization based on the improved weighted centroid localization algorithm-Particle swarm optimization based on the improved weighted centroid localization algorithm
PSOPF_localization
- 带惩罚函数的约束粒子群优化问题，在无线传感器网络节点定位中的应用-With the penalty function bound particle swarm optimization problems in wireless sensor network node localization
The-new-meta-heuristic-algorithm-bat
- 摘要：新型元启发式算法例如粒子群算法，萤火虫算法，和声搜索算法已经成为现今复杂的优化问题的有效解决方法。该文基于蝙 蝠的回声定位行为提出了一种新型的元启发式算法———蝙蝠算法，同时也将现有的一些算法的优点引入到该算法中。 改文对该算 法进行了详细的公式化表述并对其执行流程的作出了说明，并且将该算法与遗传算法、粒子群优化算法等算法进行了比较。仿真结 果表明,蝙蝠算法明显优于其他算法，并对进一步的研究作出了展望。-Summary: The new meta-heuristic algor
pso
- 基于粒子群优化算法的配电网故障定位方法，简单易懂，效果良好。-Particle swarm optimization (pso) algorithm is applied to distribution network fault diagnosis
qpso
- 量子粒子群算法应用。对三个水听器的位置定位，在假设水听器位置已知情况下，以及其他方法估计得到的时延，通过量子粒子群算法计算，验证量子粒子群算法的计算精度。-Quantum particle swarm optimization application. Position location of the three hydrophones in the hydrophone position assumed known case, and other methods for estimating
PSO
- 利用粒子群算法求解基于时差无源定位的非线性方程，解决非线性方程的最优化问题。(passive location based on PSO)
WUIPSO
- 应用结合风速信息的带电粒子群算法，实现在fluent仿真环境下气味源定位代码(Applying the charged particle swarm algorithm combined with wind speed information, the odor source localization code is implemented in the fluent simulation environment)
061820210119876
- 基于DV-HOP算法的无线传感器网络定位优化研究，加入PSO来优化算法，增加精确度。(The location optimization of wireless sensor networks based on DV-HOP algorithm is studied. PSO is added to optimize the algorithm to increase accuracy.)
PSO faultlocation
- 基于粒子群算法配电网故障定位算法，大家可以学习一下(Particle swarm optimization algorithm for fault location in distribution network)
PSO
- 可简单定位配电网故障，但是还需要改进，且只能适用于普通配电网(Simple location of distribution network fault)