检索结果-内蒙古大学图书馆

IEEE-MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO)

作者： Ou, Yue liu, Wenxin Yang, long long Zhao, Zhengyuan Wei, Yanyu Yang, Ziqiang Chinese Acad Sci Aerosp Informat Res Inst Beijing 100000 Peoples R China Sch UESTC Chengdu 610054 Peoples R China

ISBN: (纸本)9781728169668

In this article, we propose a classical optimization algorithm named l-bfgs to simulate the thermal behavior of electron gun for terahertz traveling-wave tubes. The l-bfgs algorithm, as a variation of Quasi-Newton optimization method, expert in dealing with the unconstrained optimization problems while keeping the stability of the calculation. Efficiency and accuracy of l-bfgs algorithm are verified by modeling the thermal behavior of an actual electron gun on MATlAB platform successfully with no breakdown. According to the simulation results, this method performs better than some reference methods in teens of computational memory usage and time cost. Our numerical conclusions indicate that it is promising for thermal analysis of electron gun, which would be useful for researchers during the design phase.

关键词： l-bfgs algorithm Electron Gun Thermal Simulation Traveling-wave Tube (TWT)

来源：评论

学校读者我要写书评

暂无评论

Optimization method of fi rst-arrival waveform inversion based on the l-bfgs algorithm

引用

Applied Geophysics 2021年第4期18卷 515-524,593,594页

作者： Zhang Kai Xu Xin liu Hong-Xing Xu Yi-Peng li Zhen-Chun Jiang Ping College of Geoscience China University of Petroleum(East China)Qingdao 266580China Research Institute of Petroleum Exploration and Development-Northwest Lanzhou 730000China Exploration and Development Department of China United Coalbed Methane Co. Ltd.Beijing 100011China College of Science China University of Petroleum(East China)Qingdao 266580China.

The fi rst arrival waveform inversion(FAWI)has a strong nonlinearity due to the objective function using l2 *** the initial velocity is not accurate,the inversion can easily fall into local *** the full waveform inversion method,adding a cross-correlation function to the objective function can eff ectively reduce the nonlinearity of the inversion *** this paper,the nonlinearity of this process is reduced by introducing the correlation objective function into the FAWI and by deriving the corresponding gradient *** then combine the first-arrival wave travel-time tomography with the FAWI to form a set of inversion *** paper uses the limited memory Broyden-Fletcher-Goldfarb-Shanno(l-bfgs)algorithm to improve the computational effi ciency of inversion and solve the problem of the low effi ciency of the FAWI *** overthrust model and fi eld data test show that the method used in this paper can eff ectively reduce the nonlinearity of inversion and improve the inversion calculation effi ciency at the same time.

关键词： first-arrival travel-time tomography first-arrival waveform inversion cross-correlation objective function l-bfgs algorithm

来源：评论

学校读者我要写书评

暂无评论

Study of frequency domain full waveform inversion based on Huber norm and l-bfgs algorithm

引用

Global Geology 2014年第4期17卷 238-242页

作者： WEI Yajie HAN liguo DUAN Chaoran WANG Hongye GUO Kun College of Geo-Exploration Science and Technology Jilin University

Full waveform inversion( FWI) is a high resolution inversion method,which can reveal detailed information of the structure and lithology under complex geological background. It is limited by many kinds of noises when the method applied to the real seismic data. Based on Huber function criterion,the objective function combinates the anti-noise of l1 norm and the stability of l2 norm in theory,the authors derive the gradient formula of the Huber function by using l-bfgs algorithm for FWI. The new method is proved by synthetic seismic data with the Gaussian noise and the impulse noise. Numerical test results show that l-bfgs algorithm is applied to the frequency domain FWI with the convergence speed and high calculation accuracy,and can effectively reduce computer memory usage; and the Huber function is more robust and stable than l2 norm even with the noises.

关键词： full waveform inversion Huber function l-bfgs algorithm anti-noise

来源：评论

学校读者我要写书评

暂无评论

Unsupervised learning for efficiently distributing EVs charging loads and traffic flows in coupled power and transportation systems

引用

APPlIED ENERGY 2025年第PartB期377卷

作者： Qian, Tao liang, Zeyu Shao, Chengcheng Guo, Zishan Hu, Qinran Wu, Zaijun Southeast Univ Sch Elect Engn Nanjing Peoples R China Xi An Jiao Tong Univ Sch Elect Engn Xian Peoples R China Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian Peoples R China

With the escalating adoption of electric vehicles (EVs), the intricate interplay between power and traffic systems becomes increasingly pronounced. Understanding the distribution of charging loads and traffic flows are paramount for effective coordination. Traditionally, the distribution of EVs charging loads and traffic flows are obtained via solving the EVs traffic assignment problem with User Equilibrium (TAP-UE). Despite the general convexity of TAP-UE, the iterative nature of the prevailing solution process and the nonlinear objective function pose challenges, leading to prolonged solution times. This paper introduces a novel unsupervised learning-based framework aimed at efficiently distributing EVs charging loads and traffic flows without off- the-shelf solvers or a large dataset. Firstly, feasible paths are identified for each OD pair, eliminating the need for iterative procedures. Subsequently, the convexity-preserving reformulation of TAP-UE converts it into an unconstrained nonlinear optimization problem, leading to a properly designed loss function to guide neural networks in directly learning a legitimate OD demands-EVs loads-traffic flows mapping which satisfies the UE conditions. The incorporation of the Hessian matrix into the gradient update of network parameters, facilitated by the limited-memory Broyden-Fletcher-Goldfarb-Shanno (l-bfgs) algorithm, enhances the convergence speed of the unsupervised learning process. Case studies are conducted to demonstrate the efficacy of the proposed framework.

关键词： EVs charging loads Traffic assignment problem User equilibrium Unsupervised learning l-bfgs algorithm

来源：评论

学校读者我要写书评

暂无评论

A conditional random field framework for language process in product review mining

引用

MUlTIMEDIA TOOlS AND APPlICATIONS 2023年第1期82卷 803-817页

作者： Ming, Yue liu, Xiyuan Shen, Gang Gao, Di Wang, Yu Syngenta Seeds LLC Basel Switzerland Louisiana Tech Univ Dept Math & Stat Ruston LA 71270 USA North Dakota State Univ Dept Stat Fargo ND USA Sam Houston State Univ Dept Math & Stat Huntsville TX 77340 USA Texas A&M Univ Dept Stat College Stn TX 77843 USA

The Part-Of-Speech tagging is widely used in the natural language process. There are many statistical approaches in this area. The most popular one is Hidden Markov Model. In this paper, an alternative approach, linear-chain Conditional Random Fields, is introduced. The Conditional Random Fields is a factor graph approach that can naturally incorporate arbitrary, non-independent features of the input without conditional independence among the features or distributional assumptions of inputs. This paper applied the Conditional Random Fields for the car review word Part-Of-Speech tagging and then the feature extraction, which can be used as an input to an opinion mining system. To reduce the computational time, we also proposed applying the limited-memory bfgs algorithm to train the Conditional Random Fields. Furthermore, this paper evaluated the Conditional Random Fields and the classical graph approach using the car review dataset to demonstrate that the Conditional Random Fields have a more robust result with a smaller training dataset.

关键词： Conditional Random Fields (CRFs) Natural language processing POS tagging Text mining HMM l-bfgs algorithm

来源：评论

学校读者我要写书评

暂无评论

GPU-Assisted Computation of Centroidal Voronoi Tessellation

引用

IEEE TRANSACTIONS ON VISUAlIZATION AND COMPUTER GRAPHICS 2011年第3期17卷 345-356页

作者： Rong, Guodong liu, Yang Wang, Wenping Yin, Xiaotian Gu, Xianfeng David Guo, Xiaohu Univ Texas Richardson Dept Comp Sci Richardson TX 75083 USA INRIA Lorraine LORIA Alice Project Team F-54600 Villers Les Nancy France Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

Centroidal Voronoi tessellations (CVT) are widely used in computational science and engineering. The most commonly used method is lloyd's method, and recently the l-bfgs method is shown to be faster than lloyd's method for computing the CVT. However, these methods run on the CPU and are still too slow for many practical applications. We present techniques to implement these methods on the GPU for computing the CVT on 2D planes and on surfaces, and demonstrate significant speedup of these GPU-based methods over their CPU counterparts. For CVT computation on a surface, we use a geometry image stored in the GPU to represent the surface for computing the Voronoi diagram on it. In our implementation a new technique is proposed for parallel regional reduction on the GPU for evaluating integrals over Voronoi cells.

关键词： Centroidal Voronoi tessellation graphics hardware lloyd's algorithm l-bfgs algorithm remeshing

来源：评论

学校读者我要写书评

暂无评论

A wavelet multi-scale method for the inverse problem of diffuse optical tomography

引用

JOURNAl OF COMPUTATIONAl AND APPlIED MATHEMATICS 2015年 289卷 267-281页

作者： Dubot, Fabien Favennec, Yann Rousseau, Benoit Rousse, Daniel R. Ecole Technol Super Chaire Rech Ind Technol Energie & Efficacite Ener Montreal PQ H3C 1K3 Canada LTN UMR CNRS 6607 F-44306 Nantes 3 France

This paper deals with the estimation of optical property distributions of participating media from a set of light sources and sensors located on the boundaries of the medium. This is the so-called diffuse optical tomography problem. Such a non-linear ill-posed inverse problem is solved through the minimization of a cost function which depends on the discrepancy, in a least-square sense, between some measurements and associated predictions. In the present case, predictions are based on the diffuse approximation model in the frequency domain while the optimization problem is solved by the l-bfgs algorithm. To cope with the local convergence property of the optimizer and the presence of numerous local minima in the cost function, a wavelet multi-scale method associated with the l-bfgs method is developed, implemented, and validated. This method relies on a reformulation of the original inverse problem into a sequence of sub-inverse problems of different scales using wavelet transform, from the largest scale to the smallest one. Numerical results show that the proposed method brings more stability with respect to the ordinary l-bfgs method and enhances the reconstructed images for most of initial guesses of optical properties. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Optical tomography Wavelet multi-scale method Inversion l-bfgs algorithm Optical properties

来源：评论

学校读者我要写书评

暂无评论

A Maximum A Posteriori Probability and Time-Varying Approach for Inferring Gene Regulatory Networks from Time Course Gene Microarray Data

引用

IEEE-ACM TRANSACTIONS ON COMPUTATIONAl BIOlOGY AND BIOINFORMATICS 2015年第1期12卷 123-135页

作者： Chan, Shing-Chow Zhang, li Wu, Ho-Chun Tsui, Kai-Man Univ Hong Kong Dept Elect & Elect Engn Pokfulam Hong Kong Peoples R China

Unlike most conventional techniques with static model assumption, this paper aims to estimate the time-varying model parameters and identify significant genes involved at different timepoints from time course gene microarray data. We first formulate the parameter identification problem as a new maximum a posteriori probability estimation problem so that prior information can be incorporated as regularization terms to reduce the large estimation variance of the high dimensional estimation problem. Under this framework, sparsity and temporal consistency of the model parameters are imposed using l-1-regularization and novel continuity constraints, respectively. The resulting problem is solved using the l-bfgs method with the initial guess obtained from the partial least squares method. A novel forward validation measure is also proposed for the selection of regularization parameters, based on both forward and current prediction errors. The proposed method is evaluated using a synthetic benchmark testing data and a publicly available yeast Saccharomyces cerevisiae cell cycle microarray data. For the latter particularly, a number of significant genes identified at different timepoints are found to be biological significant according to previous findings in biological experiments. These suggest that the proposed approach may serve as a valuable tool for inferring time-varying gene regulatory networks in biological studies.

关键词： Gene regulatory networks (GRNs) time course data analysis MAP estimation l-1-regularization l-bfgs algorithm partial least squares regression nonlinear optimization forward validation

来源：评论

学校读者我要写书评

暂无评论

Hybrid modelling routine for metal-oxide TFTs based on particle swarm optimisation and artificial neural network

引用

ElECTRONICS lETTERS 2020年第9期56卷 453-455页

作者： Peng You Deng Wanling Wu Weijing luo Zhi Huang Junkai Jinan Univ Dept Elect Engn Guangzhou 510630 Peoples R China South China Univ Technol State Key Lab Luminescent Mat & Devices Guangzhou 510640 Peoples R China

An effective and robust hybrid algorithm consisting of particle swarm optimisation (PSO) and limited memory Broyden-Fletcher-Goldfarb-Shanno (l-bfgs) method based on artificial neural network (ANN) is proposed for modelling flexible metal-oxide thin-film transistors (TFTs). The l-bfgs method as an optimiser is exploited to update the parameters of ANN and speed up the training process. A mutation strategy for PSO is derived to enhance the searching ability further. With the great global searching ability, PSO is implemented to find a hopeful initial position in solution space for the next ANN model. The simulation result shows a high accuracy not only in I-V curve fitting but also in small-signal parameter ($g_m$gm, $g_d$gd, etc.) predictions, which have not been exposed in the training process. The measured DC characteristics of In-Zn-O TFTs are used to verify the proposed ANN model, which has the benefits of rapid fitting from the l-bfgs algorithm and universal searching ability from PSO.

关键词： curve fitting thin film transistors neural nets optimisation particle swarm optimisation particle swarm optimisation artificial neural network effective hybrid algorithm robust hybrid algorithm PSO flexible metal-oxide thin-film transistors l-bfgs method optimiser training process great global searching ability ANN model l-bfgs algorithm universal searching ability hybrid modelling routine metal-oxide TFTs

来源：评论

学校读者我要写书评

暂无评论

Approximate solution of KdV-Burgers equation using improved PINNs algorithm

引用

INDIAN JOURNAl OF PURE & APPlIED MATHEMATICS 2024年 1-14页

作者： Kumar, Harender Yadav, Neha Natl Inst Technol Hamirpur Dept Math & Sci Comp Hamirpur 177001 HP India Dr BR Ambedkar Natl Inst Technol Dept Math Jalandhar 144011 Punjab India

Finding solutions to partial differential equations (PDEs) has long been a challenging endeavor. Despite various proposed methods, there isn't a universal approach capable of solving all types of PDEs. Recently, deep learning methods have emerged as a powerful tool for the solution of PDEs. Among them, the physics-informed neural networks (PINNs) stand out, integrating fundamental physical laws into neural networks to enforce equation dynamics using space-time data. This paper focuses on utilizing an enhanced version of the PINNs algorithm to approximate solutions for the nonlinear KdV-Burgers equation, a well-known nonlinear PDE with applications ranging from explaining wave propagation in elastic tubes filled with fluid to modeling waves in shallow viscous fluids. Our experiments yield promising results, showcased in the numerical section, where we systematically compare the performance of the PINNs method against our improved variant for each problem instance.

关键词： Physics informed neural network KdV-Burgers equation Adaptive activation function l-bfgs algorithm Chebfun package

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：