Search - particle swarm optimization

Search - particle swarm optimization - List

[VC/MFC] 35738637psotb-beta DL : 0: 标准微粒群算法用Visual c实现的希望大家能够有所用 -Standard Particle Swarm Optimization with Visual c realize the hope that we can be used
Date : 2025-12-30 Size : 53kb User : ren peng
[VC/MFC] swam DL : 0: 该电子书介绍智能算法近年来的发展情况，重点介绍粒子群算法，是初学者的一本好书-The book describes the development of intelligent algorithms in recent years, focusing on particle swarm optimization, is a good book for beginners
Date : 2025-12-30 Size : 1.88mb User : ypz
[VC/MFC] Particle-swarm-algorithm DL : 0: 微粒群算法，人工神经网络的优化，微粒群算法在函数优化中的应用 -Particle swarm algorithm, artificial neural network optimization, particle swarm algorithm in the application of function optimization
Date : 2025-12-30 Size : 1.7mb User : ndd666666
[VC/MFC] QPSO DL : 0: 提出了一种基于QPSO(Quantum Particle Swarm Optimization)的神经网络训练算法,并对神经网络进行训练,将其结果与传统神经网络训练算法相比较,该算法具有收敛速度快,对数据离散程度高的问题更易实现全局收敛的特点。-A training algorithm of neural network based on QPSO is ProPosed,whieh train the neural network by means of the quantum Partiele swarm optimization. The algorithm show better convergent speed and better global convergent charaeteristie when dealing with more dispersed issue compared with the traditional neural network training algoritm.
Date : 2025-12-30 Size : 5.14mb User : 吴鸣
[VC/MFC] PSO DL : 0: 基于VS2010开发平台，利用粒子群算法（PSO）所实现的目标识别与跟踪-VS2010 development platform based on the use of particle swarm optimization (PSO) achieved target identification and tracking
Date : 2025-12-30 Size : 26.85mb User : 李答群
[VC/MFC] Cchaaos_annt- DL : 0: 一个集合遗传算法，蚁群算法，粒子群算法的混合算法解决TSP问题的MATLAB程序-A collection of genetic algorithm, ant colony algorithm, the hybrid particle swarm optimization algorithm to solve TSP problems MATLAB program
Date : 2025-12-30 Size : 494kb User : 相里兴
[VC/MFC] Ahybr DL : 0: A hybrid Firefly Algorithm (FA) and Pattern Search (PS) optimized fuzzy PID controller is proposed for Load Frequency Control (LFC) of multi area power systems. Initially a two area thermal system with Governor Dead Band (GDB) nonlinearity is considered and the gains of the fuzzy PID controller are optimized employing a hybrid FA and PS (hFA–PS) optimization technique. The supremacy of proposed hFA–PS over FA is also demonstrated. The advantage of the proposed fuzzy PID controller has been shown by comparing the results with some recently published techniques, such as Differential Evolution (DE) and Craziness based Particle Swarm Optimization (CPSO). Further, sensitivity analysis is performed by varying the system parameters and operat
Date : 2025-12-30 Size : 660kb User : yangs