Hot Search : Source embeded web remote control p2p game More...
Location : Home Search - Optimization of process by genetic algorithm
Search - Optimization of process by genetic algorithm - List
tinyos 蚁群算法(ant colony optimization, ACO),又称蚂蚁算法,是一种用来在图中寻找优化路径的机率型算法。它由Marco Dorigo于1992年在他的博士论文中提出,其灵感来源于蚂蚁在寻找食物过程中发现路径的行为。蚁群算法是一种模拟进化算法,初步的研究表明该算法具有许多优良的性质.针对PID控制器参数优化设计问题,将蚁群算法设计的结果与遗传算法设计的结果进行了比较,数值仿真结果表明,蚁群算法具有一种新的模拟进化优化方法的有效性和应用价值-The tinyos ant colony algorithm (ant colony optimization, ACO), also known as ant algorithm the the probability type algorithm is a method for finding the optimal path in the graph. By Marco Dorigo in his doctoral thesis in 1992, inspired by the behavior of ants found in the process of looking for food path. Ant colony algorithm is a simulated evolutionary algorithm, preliminary studies show that the algorithm has many excellent properties for the PID controller parameters to optimize the design problem, the design of ant colony algorithm and genetic algorithm design compared with numerical simulation results The results show that the ant colony algorithm with a new simulated evolutionary optimization method effectiveness and value
Date : 2025-12-28 Size : 484kb User : Sofunzhao
CodeBus is one of the largest source code repositories on the Internet!
Contact us :
1999-2046 CodeBus All Rights Reserved.