The study of the identification of Sleeping Beauty literature and the dynamic law of the author’s h index can observe the Sleeping Beauty literature from multiple dimensions and provide important reference value for ...The study of the identification of Sleeping Beauty literature and the dynamic law of the author’s h index can observe the Sleeping Beauty literature from multiple dimensions and provide important reference value for the exploration of the awakening elements of Sleeping Beauty literature from the perspective of author’s influence.展开更多
This paper presents a non-parametric topic model that captures not only the latent topics in text collections, but also how the topics change over space. Unlike other recent work that relies on either Gaussian assumpt...This paper presents a non-parametric topic model that captures not only the latent topics in text collections, but also how the topics change over space. Unlike other recent work that relies on either Gaussian assumptions or discretization of locations, here topics are associated with a distance dependent Chinese Restaurant Process(ddC RP), and for each document, the observed words are influenced by the document's GPS-tag. Our model allows both unbound number and flexible distribution of the geographical variations of the topics' content. We develop a Gibbs sampler for the proposal, and compare it with existing models on a real data set basis.展开更多
基于Hgstrm(1996)和Beljaars et al.(1991)的研究工作,沿用Louis et al.(1982)和Launiainen(1995)的思路,本文采用多元回归分析方法,研发了一种采用非迭代方法的湍流通量参数化方案。该方案直接用整体理查森数、空气动力学粗糙度长...基于Hgstrm(1996)和Beljaars et al.(1991)的研究工作,沿用Louis et al.(1982)和Launiainen(1995)的思路,本文采用多元回归分析方法,研发了一种采用非迭代方法的湍流通量参数化方案。该方案直接用整体理查森数、空气动力学粗糙度长度和热力学粗糙度长度对稳定度参数进行参数化,从而避免了通过循环迭代计算Monin-Obukhov长度。该方案不仅有效地节省了CPU计算时间,而且其计算结果与迭代方案(BHH方案)的计算结果非常接近。展开更多
In this paper, auxiliary function method for global optimization with box constraints is considered. First, a new non-parameter filled function which has the same local minimizers of the objective function is proposed...In this paper, auxiliary function method for global optimization with box constraints is considered. First, a new non-parameter filled function which has the same local minimizers of the objective function is proposed. By the character that having same local minimizers, and these minimizers are all better than the current minimizer of the objective function, it does not need to minimize the objective function except for thefirst iteration in the filled function method. It changes the frame of conventional filled function methods that objective function and filled function are minimized alternately,and can effectively reduce the iterations of the algorithm and accelerate the speed of global optimization. And then the theoretical properties of the filled function are discussed and the corresponding algorithm is established. Finally, numerical experiments are made and comparisons on several test problems are shown which exhibit the feasibility and effectiveness of the algorithm.展开更多
In the paper,to solve the global optimization problems,we propose a novel parameter-free filled function.Based on the non-parameter filled function,a new filled function algorithm is designed.In the algorithm,the sele...In the paper,to solve the global optimization problems,we propose a novel parameter-free filled function.Based on the non-parameter filled function,a new filled function algorithm is designed.In the algorithm,the selection and adjustment of parameters can be ignored by the characteristic that the filled function is parameter-free.In addition,in the region lower than the current local minimizer of the objective function,the filled function is continuously differentiable which enables any gradient descent method to be used as a local search method in the algorithm.Through numerical experiments by solving two test problems,the effectiveness of the algorithm is verified.展开更多
文摘The study of the identification of Sleeping Beauty literature and the dynamic law of the author’s h index can observe the Sleeping Beauty literature from multiple dimensions and provide important reference value for the exploration of the awakening elements of Sleeping Beauty literature from the perspective of author’s influence.
基金Supported by National High Technology Research and Development Program of China(No.2012AA011005)
文摘This paper presents a non-parametric topic model that captures not only the latent topics in text collections, but also how the topics change over space. Unlike other recent work that relies on either Gaussian assumptions or discretization of locations, here topics are associated with a distance dependent Chinese Restaurant Process(ddC RP), and for each document, the observed words are influenced by the document's GPS-tag. Our model allows both unbound number and flexible distribution of the geographical variations of the topics' content. We develop a Gibbs sampler for the proposal, and compare it with existing models on a real data set basis.
文摘基于Hgstrm(1996)和Beljaars et al.(1991)的研究工作,沿用Louis et al.(1982)和Launiainen(1995)的思路,本文采用多元回归分析方法,研发了一种采用非迭代方法的湍流通量参数化方案。该方案直接用整体理查森数、空气动力学粗糙度长度和热力学粗糙度长度对稳定度参数进行参数化,从而避免了通过循环迭代计算Monin-Obukhov长度。该方案不仅有效地节省了CPU计算时间,而且其计算结果与迭代方案(BHH方案)的计算结果非常接近。
基金Supported by National Natural Science Foundation of China (Grant No. 11471102, 11701150,12071112)Basic research projects for key scientific research projects in Henan Province (Grant No. 20ZX001)。
文摘In this paper, auxiliary function method for global optimization with box constraints is considered. First, a new non-parameter filled function which has the same local minimizers of the objective function is proposed. By the character that having same local minimizers, and these minimizers are all better than the current minimizer of the objective function, it does not need to minimize the objective function except for thefirst iteration in the filled function method. It changes the frame of conventional filled function methods that objective function and filled function are minimized alternately,and can effectively reduce the iterations of the algorithm and accelerate the speed of global optimization. And then the theoretical properties of the filled function are discussed and the corresponding algorithm is established. Finally, numerical experiments are made and comparisons on several test problems are shown which exhibit the feasibility and effectiveness of the algorithm.
文摘In the paper,to solve the global optimization problems,we propose a novel parameter-free filled function.Based on the non-parameter filled function,a new filled function algorithm is designed.In the algorithm,the selection and adjustment of parameters can be ignored by the characteristic that the filled function is parameter-free.In addition,in the region lower than the current local minimizer of the objective function,the filled function is continuously differentiable which enables any gradient descent method to be used as a local search method in the algorithm.Through numerical experiments by solving two test problems,the effectiveness of the algorithm is verified.
