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边界光滑性
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  “边界光滑性”译为未确定词的双语例句
     Bayesian Multivariate Linear Splines(BMLS) is a piecewise linear regression using Bayesian methods to achieve boundary smoothness between pieces.
     贝叶斯多元线性样条BMLS是基于贝叶斯框架下的分段线性回归技术,实现了回归面边界光滑性
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  相似匹配句对
     Boundary thinking
     边界沉思
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     The Boundary of Fusion
     融合的边界
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     Smoothness of Orlicz Spaces
     Orlicz空间的光滑性
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     SMOOTHNESS OF BANACH SPACES
     Banach空间的光滑性
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  smoothness of the boundary
Our main results hold for non-constant mean curvature, and make no assumptions about the smoothness of the boundary or boundary data.
      
The smoothness of the boundary is essential: A counterexample shows that C1-smoothness is not sufficient.
      
Smoothness of the boundary function of a holomorphic function of bounded type
      
The previous result of the author on the C1 smoothness of the boundary ?N of the noncoincidence set is improved.
      
The requirements on the smoothness of the boundary of a domain are weakened.Bibliography: 16 titles.
      
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By using the tools of the module of continuity and modulus of continuity in P-mean, this paper discusses the conformal mapping from a unit circle onto a simply connected region enclosed by a smooth Jordan curve, about the smooth property of the boarder of which there are the Kellogg′s theorem and its extended Warschawski′s theorem. This paper concentrates on making deeper discussions on the original results of these theorems and obtains more general results.

从单位圆到以光滑 Jordan曲线为边界的单连通区域的共形映射 ,其边界的光滑性有经典的Kellogg定理及其推广的 Warschawski定理 ,本文以连续模、P次平均模为工具对原结果进行了深入的讨论 ,得到了更为一般的结果 .

By using the tools of the module of continuity, this paper discusses the conformal mapping from a unit circle onto a simply connected region enclosed by a smooth Jordan curve, the smooth properties of its border are illustrated by the Kellogg's theorem and its extended Warschawski's theorem. This paper concentrates on making deeper discussions on the original results of these theorems and obtains more general results.

从单位圆到以光滑 Jordan曲线为边界的单连通区域的共形映射 ,其边界的光滑性有经典的 Kel-logg定理及其推广的 Warschawski定理。以连续模为工具对原结果进行了深入的讨论 ,得到了更为一般的结果。

Bayesian Multivariate Linear Splines(BMLS) is a piecewise linear regression using Bayesian methods to achieve boundary smoothness between pieces. After discussing privary technologies used for BMLS, it is proposed to be used for mid-term load forecasting in this paper. After analyzing data from EUNITE-network-sponsoring competition, we did experiments choosing different train samples, getting good results. We compare experimental results with other methods and present some explanations. In the end of the paper...

Bayesian Multivariate Linear Splines(BMLS) is a piecewise linear regression using Bayesian methods to achieve boundary smoothness between pieces. After discussing privary technologies used for BMLS, it is proposed to be used for mid-term load forecasting in this paper. After analyzing data from EUNITE-network-sponsoring competition, we did experiments choosing different train samples, getting good results. We compare experimental results with other methods and present some explanations. In the end of the paper we do summaries on BMLS advantages and disadvantages, comparing with other methods, such as the Relevance Vector Machines, etc. Predications with analogy approximation averaging used in BMLS, can achieve better performances.

贝叶斯多元线性样条BMLS是基于贝叶斯框架下的分段线性回归技术,实现了回归面边界光滑性。本文分析了BMLS方法的原理,结合EUNITE网络2001年举办的电力负荷预测比赛提供的数据进行了相关数据分析,建立了相应的电力负荷中期预测模型。我们使用BMLS方法对两种训练样本集进行了训练,并计算出预测期的预测值,取得了理想的预测结果,并结合其它方法对试验结果进行了分析。文章最后总结了BMLS方法用于预测的特点,并与其它方法,如相关向量机等进行了比较。使用BMLS的模拟近似平均技术进行预测可以实现较好的精度。

 
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