全局优化算法 meaning in English
global optimization algorithm
Examples
- As a powerful global optimization approach , genetic algorithms ( ga ) can solve a variety of optimization problems in which the objective function is discontinuous , non - differentiable , or highly non - linear , to produce high convergence speed and vast search space
摘要遗传算法作为一种全局优化算法，可以用来解决在目标函数不连续、不可能、非线性等情况下的复杂问题，且具有较高的收敛效率和广阔的搜索空间。 - This problem has been solved through two - step . 1 ) sample data has been used to train a bp neural network based genetic algorithm ( ga ) , the model is a static model . 2 ) the reformed bp algorithm bas been used to adjust the model in real time
1 )利用实际采集的样本数据，采用遗传算法优化神经网络的初始权值，从而离线建立了电弧炉的模型；遗传算法作为全局优化算法对于解决神经网络在逼近多变量复杂模型时存在的局部最优问题有独特的作用。 - In the algorithm level , currently various training algorithms of neural networks , including gradient algorithms , intelligent learning algorithms and hybrid algorithms , are comparatively studied ; the optimization principle of bp algorithm for neural networks training is analyzed in detail , and the reasons for serious disadvantages of bp algorithms are found out , moreover , the optimization principle of two kinds of improved bp algorithms is described in a uniform theoretic framework ; and the global optimization algorithms of neural networks , mainly genetic algorithm are expounded in detail , it follows that a improved genetic algorithm is proposed ; finally the training performances of various algorithms are compared based on a simulation experiment on a benchmark problem of neural network learning , furthermore , a viewpoint that genetic algorithm is subject to " curse of dimension " is proposed
在算法层，本文对目前用于神经网络训练的各种算法，包括梯度算法、智能学习算法和混合学习算法进行了比较研究；对用于神经网络训练的bp算法的优化原理进行了详细的理论分析，找到了bp算法存在严重缺陷的原因，并对其两类改进算法-启发式算法和二次梯度算法的优化原理，在统一的框架之下进行了详尽的理论描述；对神经网络全局优化算法主要是遗传算法进行了详细的阐述，并在此基础上，设计了一种性能改进的遗传算法；最后基于神经网络学习的benchmark问题对各种算法在网络训练中的应用性能进行了仿真研究，并提出了遗传算法受困于“维数灾难”的观点。 - Thanks to the support of the national natural science foundation of china under grand no . 50277036 for " the pulse electromagnetic fields and system - level em radiation of electric vehicles " , this thesis concentrated on the design of the variable voltage and variable frequency ( vvvf ) system and the development of a genetic algorithm for vector optimal design problems . the work includes mainly four parts : a brief introduction of the frequency - converter , the emc design of the vvvf system and the national standard of the electromagnetic interference of the vvvf system , the study of global search optimization algorithms , and an improved genetic algorithm called emigration genetic algorithm for multi - objective optimal problems
在国家自然科学基金资助项目《电动汽车脉冲电磁场与系统级辐射的研究》的工作基础上，本文对电动车电磁辐射关键部分? ?变频调速系统的电磁兼容性设计以及在电磁兼容性设计中涉及到的电磁系统的多目标优化方法进行了系统的分析和研究，其核心内容包括：变频器工作原理；变频调速系统电磁兼容性设计及变频调速系统电磁兼容标准；随机类全局优化算法研究；提出了一种改进的遗传算法命名为迁徙遗传算法。 - Genetic algorithm is a widely concerned global search algorithm , which has good parallel search ability for having pioneered the implementation of methods that exploit the idea of combining solutions , while tabu search has pioneered the systematic exploration of memory functions in search processes , having good local search ability because of its flexible memory mechanism and respective tabu criteria to avoid circuit search
遗传算法是一种受到广泛关注的全局优化算法,开创了在解空间中从多出发点搜索问题最优解的先河,具有很强的并行搜索能力,而禁忌搜索算法是在搜索过程中使用记忆功能的先驱者,以其灵活的存储结构和相应的禁忌准则来避免迂回搜索,具有较强的局部搜索能力。