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Validation for building density remote sensing products of built-up areas at large scale 大规模建成区建筑密度遥感产品的验证
Pub Date : 2020-01-15 DOI: 10.7523/J.ISSN.2095-6134.2020.01.010
Wang Shuai, Qin Yuchu, Yang Fukun
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引用次数: 1
Spatiotemporal evolution of urban and rural development level and its coordination degree in Tarim Basin in recent ten years 近十年塔里木盆地城乡发展水平的时空演变及其协调程度
Pub Date : 2020-01-15 DOI: 10.7523/J.ISSN.2095-6134.2020.01.008
WU Shengqin, Yang Degang, Huo Jinwei, Wu Rongwei
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引用次数: 0
Existence and related properties of non-zero Gaussian curvature Bonnet surfaces 非零高斯曲率Bonnet曲面的存在性及相关性质
Pub Date : 2020-01-15 DOI: 10.7523/J.ISSN.2095-6134.2020.01.002
Wang Ke, Wu Yingyi
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引用次数: 0
Some methods of parameter estimation for stochastic differential equations 随机微分方程参数估计的几种方法
Pub Date : 2017-09-15 DOI: 10.7523/J.ISSN.2095-6134.2017.05.001
Cai Xinrui, Wang Lijin
We propose three methods of parameter estimation based on discrete observation data for stochastic differential equations (SDEs). The first method is designed for linear stochastic differential equations (SDEs). For these equations we deduce distribution of certain operation of the exact solution and assume that the relevant operation of the observed data obey this distribution, from which we estimate the unknown parameters in the drift and diffusion coefficients. In the second method, we suppose that certain operation of the observation data and that of the numerical solution arising from the Euler-Maruyama scheme for the SDEs of Ito sense obey the same distribution, from which the unknown parameters can be estimated. We use the third method for SDEs of Stratonovich sense. For these equations we derive the distribution of relevant operation of the numerical solution produced by the midpoint scheme and let the same operation of the data obey this distribution to get estimation of the unknown parameters. Numerical results show validity of the proposed methods, and illustrate that the estimation error produced by the Euler-Maruyama scheme is about of order O(h0.5) while that by the midpoint scheme is about of order O(h), with h being the time step size of the numerical methods. Furthermore, the numerical results show that our methods are more accurate than the existing EM-MLE estimator.
我们提出了三种基于离散观测数据的随机微分方程参数估计方法。第一种方法是为线性随机微分方程设计的。对于这些方程,我们推导出精确解的某些运算的分布,并假设观测数据的相关运算服从这种分布,由此我们估计漂移系数和扩散系数中的未知参数。在第二种方法中,我们假设观测数据的某些运算和由Euler Maruyama格式产生的Ito意义SDE的数值解的某些运算服从相同的分布,由此可以估计未知参数。我们对Stratonovich意义上的SDE使用第三种方法。对于这些方程,我们导出了由中点格式产生的数值解的相关运算的分布,并使数据的相同运算服从该分布,以获得未知参数的估计。数值结果表明了所提出方法的有效性,并表明Euler Maruyama格式产生的估计误差约为O(h0.5)阶,而中点格式产生的误差约为0(h)阶,其中h是数值方法的时间步长。此外,数值结果表明,我们的方法比现有的EM-MLE估计更准确。
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引用次数: 0
Effect of non-condensable gas on pressure oscillation of submerged steam jet 不凝性气体对浸没蒸汽射流压力振荡的影响
Pub Date : 2017-03-15 DOI: 10.7523/J.ISSN.2095-6134.2017.02.002
Cong Yuelei, Wang Yingchun, Chen Weixiong, Chong Daotong, Yan Junjie
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引用次数: 1
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中国科学院大学学报
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