This paper introduce not only the relations between ea and other science but also the research and prospect of ea , hi order to preferably understand the states , the direction hi future and the effect of ea 为了更好地理解进化计算的地位与作用,以及将来的发展方向,在本文中,介绍了进化计算与其他学科的关系以及进化计算的研究和展望。
A new object recognition method of color image is proposed in this paper , which combines the template matching with the mind evolutionary computation ( mec ) . the recognition is done in cie 1976 luv uniform color space 本文提出一种新的目标识别算法,它是把模板匹配思想和性能优异的思维进化计算结合起来,在cie1976广矿矿均匀颜色空间上匹配。
To overcome the problems of ga , mind evolutionary computation ( mec ) was proposed by chengyi sun in 1998 , which imitates two phenomena of human society - similartaxis and dissimilation 思维进化计算是孙承意教授于1998年提出的进化计算新方法,它是根据对遗传算法( gas )存在问题的思考以及对人类思维进步的分析,模仿人类社会中存在的趋同和异化现象提出来的。
In this dissertation , evolutionary computation , a representation of intelligent control , is combined with modern robust control to be a robust algorithm for multi - agent systems . meanwhile , the theoretical frame is also built 本博士学位论文将以进化计算为代表的智能控制方法与现代鲁棒控制方法相结合,提出与实现了多智能体系统的鲁棒算法,建立了理论框架。
Hierarchy theory is introduced to interactive evolutionary computation and hierarchical interactive evolutionary computation is put forth aiming at inefficient local search problem of the existing interactive evolutionary computation 摘要针对目前交互式进化计算存在的局部搜索能力不强、效率低下等问题,将分层的思想引入交互式进化计算,提出了分层交互式进化计算。
In view to that , with the aid of a newly developed evolutionary computation technology , namely , genetic programming , it is significative to study the identification of certain nonmonotonic nonlinear systems based on genetic programming 针对上述情况,借助于新兴的进化计算遗传编程方法,研究基于遗传编程技术的对某类非单调、非线性系统的辨识方法具有十分重要的意义。
On the other hand , by combining fuzzy logic , evolutionary computation and stochastic optimal methods , structure and learning algorithms of neural networks are studied for neural control , which is one of the important branches of intelligent control 而通过对神经网络的结构和学习算法的研究,结合模糊逻辑、进化计算和随机优化等方法,探讨了智能控制中的重要的分支? ?神经网络控制的有关理论与技术。
The results of the experiments show that , when there are different kinds of differences in lightness , zoom and angle between matching model and matched image , this kind of optimization algorithm based on evolutionary computation can solve the problem effectively 实验结果证明,当待匹配图像和匹配模板之间存在亮度、大小缩放和旋转角度差异的情况下,这种基于进化计算的图像匹配算法能够进行正确匹配。
Being a new kind of general problem - solving paradigm inspired by the principle of biology evolution , evolutionary computation ( ec ) is meanly used for solving optimization problem , and has found great many of successful applications in machine learning ( ml ) 智能决策技术面临前所未有的挑战和机遇。进化计算是一种借鉴生物进化机制求解优化类问题的新型广谱问题求解范型,在机器学习等领域有着广泛的应用。
Particle swarm optimization ( pso ) is inspired by social behavior of bird flocking or fish schooling . it is a population - based , self - adaptive search optimization technique . pso is simple in concept , few in parameters , and easy in implementation 粒子群优化算法( particleswarmoptimization , pso算法)源于鸟群和鱼群群体运动行为的研究,是一种基于种群搜索策略的自适应随机算法,是进化计算领域中的一个新的分支。