edas
- 网络分布估计算法
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In this thesis , we propose a general ap-proach to analyzing the time complexity of EDAs .
本文为分布评估算法的时间复杂度分析提出一种一般性的研究思路。
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In contrast to traditional estimate distribution algorithm , parallel EDAs has greatly improved the efficiency when optimizing continuous functions and real time questions .
相对于传统的概率分布估计算法,并行的概率分布估计算法在解决连续函数优化及实时优化问题时能提供极大程度的效率提高。
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Later the core of EDAs - probability map model was introduced and Bayesian network structure ( Bayesian Beliefs Networks ) was emphasized .
然后介绍了概率分布估计算法的核心&概率图模型;
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Estimation of Distribution Algorithms ( EDAs ) are new evolutionary algorithms based on probabilistic model and have become a new focus in the field of evolutionary computation .
分布估计算法由于其较强的理论基础已成为进化计算研究的新热点。
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Optimization of the hyper-parameters in GP surrogate modeling based on EDAs is proposed , which can solve the problem of local search algorithms .
本文提出基于分布估计算法的高斯过程建模超参数优化算法,该算法能够克服局部搜索算法陷入局部最优的缺点。
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Cases in this study showed that the Suzuki stage of preoperative DSA was rank correlation with the extent of revascularization after EDAS . 5 .
本组病例显示术前DSA铃木分期与EDAS术后手术血管重建情况间存在等级相关关系。
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Investigation on 115 EDAs
115名教育硕士的调查研究
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They are sequentially the introduction , literature review , the theoretical framework for this thesis , the contrastive analysis of appraisal resources in EDAs and CDAs and the conclusion .
依次为引言、文献综述、论文理论框架、评价理论下中英文约会广告的评价资源对比分析和文章结论。
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In recently years , EDAs have become a hot topic in field of evolutionary computation , which attract a large number of scholars carried on the theoretical research and application of optimization about them .
分布估计算法经提出以后,迅速成为进化计算领域的研究热点,大量学者对其进行了理论研究和优化应用。
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This study showed that cortical microvascular density of patients with MMD was rank correlation with improvement of clinical symptoms , improvement of cerebral metabolism , and the extent of revascularization after EDAS .
本研究显示MMD患者皮层微血管密度与EDAS术后患者临床症状改善程度、脑代谢改善程度、手术血管重建情况间存在等级相关关系。
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The results of Auger Electron Spectroscopy ( AES ) and Energy Dispersive Analysis X-ray Spectroscopy ( EDAS ) measurements show that the interface layer contains Au-Ga intermetallic compound and impurity P , Si .
借助俄歇能谱(AES)和能量色散谱(EDAS)初步分析了Au-Si/n-GaP系统接触的界面含有Au-Ga金属间化合物以及P和Si杂质。
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Estimation of distribution algorithms ( EDAs ) are a type of evolutionary algorithms based on probability models . Because of the excellent performance of EDAs on optimization problems and the model interpretation , EDAs are receiving more interest in recent years .
分布估计算法(EstimationofDistributionAlgorithms,EDAs)是一类以概率模型为基础的进化算法,由于其突出的问题优化能力与模型的解释能力,近年来这类算法也受到了广泛的关注。
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Estimation of distribution algorithms ( EDAs ) are a new kind of colony evolution algorithms , through counting the excellent information of the individuals of present colony EDAs construct a probability distribution model , then sample the model to produce the next generation .
分布估计算法是一种新的基于种群进化的算法,它通过统计当前群体中较优个体的信息构建其概率分布模型,然后对模型进行抽样生成下一代群体。
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However , most investigations were carried out on the basis of empirical observations . Although some scholars have concerned the convergence properties of EDAs , there is no investigation that analyzes successfully the time complexity of population-based EDAs by rigorous mathematical discussions .
虽然有少量研究者关注种群分布评估算法的收敛性,但还没有研究者成功地对这类算法的时间复杂度进行过严密的理论研究。