Search - Fish swarm optimization

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[Other] 333 DL : 0: 摘要:在分析人工鱼群算法存在不足的基础上,对人工鱼群算法加以改进,提出了一种改进型人工鱼群算法。该算法提高了全局搜索能力和收敛速度,并用于求解具有变量边界约束的非线性复杂函数最优化问题。仿真结果表明,改进后的人工鱼群算法具有精度高、搜索速度快等特点,是一种求解复杂函数全局最优化的智能算法 -Abstract: In analyzing the deficiencies of artificial fish-swarm algorithm based on improved artificial fish-swarm algorithm, an improved artificial fish-swarm algorithm. The algorithm improve the global search ability and convergence speed, and used to solve the border with variables constrained nonlinear optimization problem of complex functions. The simulation results show that the improved artificial fish-swarm algorithm with high precision, fast search, etc., is a complex function for solving global optimization of the intelligent algorithm
Date : 2025-12-16 Size : 185kb User : duweijie
[Other] psopt20130502b DL : 0: Particle swarm optimization is a derivative-free global optimum search algorithm based on the collective intelligence of a large group of intercommunicating entities. The individual particles are simple and primitive, knowing only their own current locations and fitness values, their personal best locations, and the swarm s best location. Each particle continually adjusts its trajectory based this information, moving towards the global optimum with each iteration. The swarm as a whole displays a remarkable level of coherence and coordination despite the simplicity of its individual particles. The coordinated behavior of the swarm has been compared with that of a flock of birds or a school of fish.
Date : 2025-12-16 Size : 33kb User : ouchi
[Other] 1 DL : 0: 智能优化算法作为新兴的搜索算法，一般是指利用自然界的生物系统与优化过程的某些相似性而逐步发展起来的优化算法，如遗传算法、粒子群算法、蚁群算法等，它们通过对搜索空间中的一组解按概率规则操作得到下一组解。人工鱼群算法源于对鱼群运动行为的研究，是一种新型的智能仿生优化算法。它具有较强的鲁棒性、优良的分布式计算机制、易于和其它方法结合等优点。目前对该算法的研究、应用已经渗透到多个应用领域，并由解决一维静态优化问题发展到解决多维动态组合优化问题。 -As an emerging intelligent optimization algorithms search algorithm, generally refers to the use of natural biological systems and the optimization process some similarities and gradually developed optimization algorithms, such as genetic algorithms, particle swarm optimization, ant colony algorithm, which searches through space of solutions according to the probability of a rule action to get the next set of solutions. AFSA stems from the behavior of fish movement, is a new type of intelligent bionic optimization algorithm. It has strong robustness, excellent distributed computer system, easy to combine with other methods, etc.. At present the algorithm research, application has penetrated into multiple applications, by solving one-dimensional static optimization problem developed to solve multidimensional dynamic combinatorial optimization problems.
Date : 2025-12-16 Size : 365kb User : eggitta
[Other] ACO-PID DL : 0: 除了蚁群算法，可用于PID参数优化的智能算法还有很多，比如遗传算法、模拟退火算法、粒子群算法、人工鱼群算法，等等。-In addition to the ant colony algorithm, can be used in the intelligent algorithm of PID parameter optimization and there are many, such as genetic algorithm, simulated annealing algorithm, particle swarm optimization (pso), artificial fish algorithm, and so on.
Date : 2025-12-16 Size : 1kb User : 昊轩
[Other] APSO123 DL : 0: PSO is originally attributed to Kennedy, Eberhart and Shi[1][2] and was first intended for simulating social behaviour,[3] as a stylized representation of the movement of organisms in a bird flock or fish school. The algorithm was simplified and it was observed to be performing optimization. The book by Kennedy and Eberhart[4] describes many philosophical aspects of PSO and swarm intelligence. An extensive survey of PSO applications is made by Poli.[5][6] Recently, a comprehensive review on theoretical and experimental works on PSO has been published by Bonyadi and Michalewicz.[7]
Date : 2025-12-16 Size : 5kb User : snn
[Other] artificial-fish-swarm-algorithm DL : 0: 无约束连续函数优化的人工鱼群算法通用MATLAB源码-Uniformly continuous function optimization of artificial fish swarm algorithm
Date : 2025-12-16 Size : 2kb User : feng