期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到35篇文章
< 1 2 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Parameter selection of support vector machine for function approximation based on chaos optimization 认领 引用 被引量：20
1
作者 Yuan Xiaofang Wang Yaonan 《Journal of Systems Engineering and Electronics》 SCIE EI 2008年第1期191-197,共7页
The support vector machine(SVM)is a novel machine learning method,which has the ability to approximate nonlinear functions with arbitrary accuracy.Setting parameters well is very crucial for SVM learning results and g... The support vector machine(SVM)is a novel machine learning method,which has the ability to approximate nonlinear functions with arbitrary accuracy.Setting parameters well is very crucial for SVM learning results and generalization ability,and now there is no systematic,general method for parameter selection.In this article,the SVM parameter selection for function approximation is regarded as a compound optimization problem and a mutative scale chaos optimization algorithm is employed to search for optimal paraxneter values.The chaos optimization algorithm is an effective way for global optimal and the mutative scale chaos algorithm could improve the search efficiency and accuracy.Several simulation examples show the sensitivity of the SVM parameters and demonstrate the superiority of this proposed method for nonlinear function approximation. 展开更多
关键词 learning systems support vector machines(SVM) approximation theory parameter selection optimization.
暂未订购 下载PDF
TV/L2-based image denoisingalgorithm with automaticparameter selection 认领 引用 被引量：1
2
作者 王保宪 唐林波 +2 位作者 赵保军 邓宸伟 杨静林 《Journal of Beijing Institute of Technology》 EI CAS 2014年第3期375-382,共8页
In order to improve the adaptiveness of TV/L2-based image denoising algorithm in differ- ent signal-to-noise ratio （SNR） environments, an iterative denoising method with automatic parame- ter selection is proposed. ... In order to improve the adaptiveness of TV/L2-based image denoising algorithm in differ- ent signal-to-noise ratio （SNR） environments, an iterative denoising method with automatic parame- ter selection is proposed. Based upon the close connection between optimization function of denois- ing problem and regularization parameter, an updating model is built to select the regularized param- eter. Both the parameter and the objective function are dynamically updated in alternating minimiza- tion iterations, consequently, it can make the algorithm work in different SNR environments. Mean- while, a strategy for choosing the initial regularization parameter is presented. Considering Morozov discrepancy principle, a convex function with respect to the regularization parameter is modeled. Via the optimization method, it is easy and fast to find the convergence value of parameter, which is suitable for the iterative image denoising algorithm. Comparing with several state-of-the-art algo- rithms, many experiments confirm that the denoising algorithm with the proposed parameter selec- tion is highly effective to evaluate peak signal-to-noise ratio （PSNR） and structural similarity 展开更多
关键词 image denoising parameter selection fast gradient-based method discrepancy princi-ple
暂未订购 下载PDF
Piezoelectric transducer parameter selection for exciting a single mode from multiple modes of Lamb waves 认领 引用 被引量：2
3
作者 张海燕 于建波 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第9期262-270,共9页
Excitation and propagation of Lamb waves by using rectangular and circular piezoelectric transducers surface- bonded to an isotropic plate are investigated in this work. Analytical stain wave solutions are derived for... Excitation and propagation of Lamb waves by using rectangular and circular piezoelectric transducers surface- bonded to an isotropic plate are investigated in this work. Analytical stain wave solutions are derived for the two transducer shapes, giving the responses of these transducers in Lamb wave fields. The analytical study is supported by a numericM simulation using the finite element method. Symmetric and antisymmetric components in the wave propagation responses are inspected in detail with respect to test parameters such as the transducer geometry, the length and the excitation frequency. By placing only one piezoelectric transducer on the top or the bottom surface of the plate and weakening the strength of one mode while enhancing the strength of the other modes to find the centre frequency, with which the peak wave amplitude ratio between the SO and A0 modes is maximum, a single mode excitation from the multiple modes of the Lamb waves can be achieved approximately. Experimental data are presented to show the validity of the analyses. The results are used to optimize the Lamb wave detection system. 展开更多
关键词 Lamb waves parameter selection analytical stain wave solutions single mode
暂未订购 下载PDF
Parameter selection in time series prediction based on nu-support vector regression 认领 引用
4
作者 胡亮 Che Xilong 《High Technology Letters》 EI CAS 2009年第4期337-342,共6页
The theory of nu-support vector regression (Nu-SVR) is employed in modeling time series variationfor prediction. In order to avoid prediction performance degradation caused by improper parameters, themethod of paralle... The theory of nu-support vector regression (Nu-SVR) is employed in modeling time series variationfor prediction. In order to avoid prediction performance degradation caused by improper parameters, themethod of parallel multidimensional step search (PMSS) is proposed for users to select best parameters intraining support vector machine to get a prediction model. A series of tests are performed to evaluate themodeling mechanism and prediction results indicate that Nu-SVR models can reflect the variation tendencyof time series with low prediction error on both familiar and unfamiliar data. Statistical analysis is alsoemployed to verify the optimization performance of PMSS algorithm and comparative results indicate thattraining error can take the minimum over the interval around planar data point corresponding to selectedparameters. Moreover, the introduction of parallelization can remarkably speed up the optimizing procedure. 展开更多
关键词 parameter selection time series prediction nu-support vector regression （Nu-SVR） parallel multidimensional step search （PMSS）
暂未订购 下载PDF
Parameter selection and model research on remote sensing evaluation for nearshore water quality 认领 引用 被引量：1
5
作者 LEI Guibin ZHANG Ying +2 位作者 PAN Delu WANG Difeng FU Dongyang 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2016年第1期114-117,共4页
Using remote sensing technology for water quality evaluation is an inevitable trend in marine environmental monitoring. However, fewer categories of water quality parameters can be monitored by remote sensing technolo... Using remote sensing technology for water quality evaluation is an inevitable trend in marine environmental monitoring. However, fewer categories of water quality parameters can be monitored by remote sensing technology than the 35 specified in GB3097-1997 Marine Water Quality Standard. Therefore, we considered which parameters must be selected by remote sensing and how to model for water quality evaluation using the finite parameters. In this paper, focused on Leizhou Peninsula nearshore waters, we found N, P, COD, PH and DO to be the dominant parameters of water quality by analyzing measured data. Then, mathematical statistics was used to determine that the relationship among the five parameters was COD〉DO〉P〉N〉pH. Finally, five-parameter, fourparameter and three-parameter water quality evaluation models were established and compared. The results showed that COD, DO, P and N were the necessary parameters for remote sensing evaluation of the Leizhou Peninsula nearshore water quality, and the optimal comprehensive water quality evaluation model was the four- parameter model. This work may serve as a reference for monitoring the quality of other marine waters by remote sensing. 展开更多
关键词 main water quality parameters water quality parameter selection comprehensive water qualityevaluation model Leizhou Peninsula nearshore waters
暂未订购 下载PDF
Convolution Neural Network-based Load Model Parameter Selection Considering Short-term Voltage Stability 认领 引用 被引量：2
6
作者 Ying Wang Chao Lu Xinran Zhang 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2024年第3期1064-1074,共11页
The recently proposed ambient signal-based load modeling approach offers an important and effective idea to study the time-varying and distributed characteristics of power loads.Meanwhile,it also brings new problems.S... The recently proposed ambient signal-based load modeling approach offers an important and effective idea to study the time-varying and distributed characteristics of power loads.Meanwhile,it also brings new problems.Since the load model parameters of power loads can be obtained in real-time for each load bus,the numerous identified parameters make parameter application difficult.In order to obtain the parameters suitable for off-line applications,load model parameter selection(LMPS)is first introduced in this paper.Meanwhile,the convolution neural network(CNN)is adopted to achieve the selection purpose from the perspective of short-term voltage stability.To begin with,the field phasor measurement unit(PMU)data from China Southern Power Grid are obtained for load model parameter identification,and the identification results of different substations during different times indicate the necessity of LMPS.Meanwhile,the simulation case of Guangdong Power Grid shows the process of LMPS,and the results from the CNNbased LMPS confirm its effectiveness. 展开更多
关键词 Ambient signal CNN field PMU data load model parameter selection short-term voltage stability
暂未订购 下载PDF
Scaling parameters selection principle for the scaled unscented Kalman filter 认领 引用 被引量：1
7
作者 NIE Yongfang ZHANG Tao 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第3期601-610,共10页
The paper deals with the state estimation of the widely used scaled unscented Kalman filter（UKF）. In particular, the stress is laid on the scaling parameters selection principle for the scaled UKF. Several problems ... The paper deals with the state estimation of the widely used scaled unscented Kalman filter（UKF）. In particular, the stress is laid on the scaling parameters selection principle for the scaled UKF. Several problems caused by recommended constant scaling parameters are highlighted. On the basis of the analyses, an effective scaled UKF is proposed with self-adaptive scaling parameters,which is easy to understand and implement in engineering. Two typical strong nonlinear examples are given and their simulation results show the effectiveness of the proposed principle and algorithm. 展开更多
关键词 nonlinear filtering scaled unscented Kalman filter scaling parameter selection principle
暂未订购 下载PDF
Novel Method for Selection of Regularization Parameter in the Near-field Acoustic Holography 认领 引用
8
作者 ZHANG Yongbin BI Chuanxing +1 位作者 XU Liang CHEN Xinzhao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2011年第2期285-292,共8页
Because of the ill-posedness of the near-field acoustic holography(NAH),the regularization method is required to stabilize the computational process of NAH.The regularization effect is related to how to select the par... Because of the ill-posedness of the near-field acoustic holography(NAH),the regularization method is required to stabilize the computational process of NAH.The regularization effect is related to how to select the parameter correctly and effectively.However the L-curve method commonly used for the selection of regularization parameters has the disadvantages of wrong selection and incorrect selection,which influences the application of NAH.For the purpose of solving the problems existed in the L-curve method,the(?)-curve method is introduced into the field of NAH,and the performance applied to NAH directly is analyzed on the basis of equivalent source method-based NAH.However,it is found out via investigations that the(?)-curve method in NAH also has the problem of wrong selection and is unable to choose the regularization parameter correctly.In order to select the parameter correctly and effectively,a novel method for selecting regularization parameters is proposed based on the original(?)-curve method,which can be called improved(?)-curve method.In the proposed method the regularization parameters are discretized linearly between the largest singular value and the smallest singular value,and the solution norm and the residual norm corresponding to these regularization parameters are also described in a linear coordinate instead of in a lg-lg coordinate,which are the two main differences compared with the L-curve and with the original(?)-curve method.In linear coordinate and using the linearly discretized regularization parameters,the solution norm is a monotonically decreasing function of the residual norm as the increase of the regularization parameter,moreover the curve is convex everywhere.So the regularization parameters can be selected correctly and effectively based on the improved(?)-curve method.Then a numerical simulation is done with a simply supported plate to verify the validity of the proposed method.Experiments with two actual sources,a clamped plate and the double speakers,are carried out to do a further demonstration.The simulation result as well as the experimental result shows that the improved(?)-curve method is efficacious and has some advantages over the L-curve method and the original(?)-curve method.The proposed novel method is able to avoid the problem of wrong selection and to select the regularization parameter correctly even if the curve is smooth. 展开更多
关键词 near-field acoustic holography(NAH) regularization parameter selection
暂未订购 下载PDF
Novel linear search for support vector machine parameter selection 认领 引用 被引量：6
9
作者 Hong-xia PANG Wen-de DONG +3 位作者 Zhi-hai XU Hua-jun FENG Qi LI Yue-ting CHEN 《Journal of Zhejiang University-Science C(Computers and Electronics)》 2011年第11期885-896,共12页
Selecting the optimal parameters for support vector machine(SVM)has long been a hot research topic.Aiming for support vector classificationegression(SVC/SVR)with the radial basis function(RBF)kernel,we summarize the r... Selecting the optimal parameters for support vector machine(SVM)has long been a hot research topic.Aiming for support vector classificationegression(SVC/SVR)with the radial basis function(RBF)kernel,we summarize the rough line rule of the penalty parameter and kernel width,and propose a novel linear search method to obtain these two optimal parameters.We use a direct-setting method with thresholds to set the epsilon parameter of SVR.The proposed method directly locates the right search field,which greatly saves computing time and achieves a stable,high accuracy.The method is more competitive for both SVC and SVR.It is easy to use and feasible for a new data set without any adjustments,since it requires no parameters to set. 展开更多
关键词 Support vector machine(SVM) Rough line rule Parameter selection Linear search Motion prediction
Monotonic Optimization with Application to the Selection of Parameters for LWE-Based Encryption Schemes 认领 引用
10
作者 XU Juan WU Wenyuan +1 位作者 FENG Yong DONG Rina 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2026年第4期1815-1838,共24页
Monotonic optimization is a special class of global optimization with applications cross fields.It addresses problems in which the objective and constraint functions are increasing w.r.t.each of the variables.In this ... Monotonic optimization is a special class of global optimization with applications cross fields.It addresses problems in which the objective and constraint functions are increasing w.r.t.each of the variables.In this work,the authors extend to the case where the objective and constraint functions are monotonic.The authors present a general framework to address such problems,and especially propose a complete algorithm that is guaranteed to terminate in finitely many steps for problems in a special form.Different from traditional optimization algorithms based on gradient descent,the proposed algorithm does not require closed-form expressions of the functions.As an important application,the functions involved in the parameter optimization problem of LWE-based encryption scheme exhibit monotonicity w.r.t.each of the variables(but may not be increasing),and certain functions involved have no closed-form expression.Inspired by the idea of mathematics mechanization,the authors formalize practical problems into mathematical models and provide a framework for developing automatic and systematic approaches to tackle the parameter optimization problems in lattice-based cryptography.As an illustrative example,the authors consider the parameter optimization of BGV scheme in the context of minimizing communication overhead,without considering homomorphic operations,and provide optimal parameters for it under specified security levels and correctness probabilities. 展开更多
关键词 Encryption scheme global optimization LWE problem monotonic functions parameter selection
暂未订购 下载PDF
Optimal choice of parameters for particle swarm optimization 认领 引用 被引量：21
11
作者 张丽平 俞欢军 胡上序 《Journal of Zhejiang University-SCIENCE A》 CAS 2005年第6期528-534,共7页
The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically inv... The constriction factor method (CFM) is a new variation of the basic particle swarm optimization (PSO), which has relatively better convergent nature. The effects of the major parameters on CFM were systematically investigated based on some benchmark functions. The constriction factor, velocity constraint, and population size all have significant impact on the per- formance of CFM for PSO. The constriction factor and velocity constraint have optimal values in practical application, and im- proper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. The characteristics of CFM parameters are described and guidelines for determining parameter values are given in this paper. 展开更多
关键词 Particle swarm optimization (PSO) Constriction factor method (CFM) Parameter selection
暂未订购 下载PDF
Individualization of Data-Segment-Related Parameters for Improvement of EEG Signal Classification in Brain-Computer Interface 认领 引用 被引量：1
12
作者 曹红宝 BESIO Walter G +1 位作者 JONES Steven 周鹏 《Transactions of Tianjin University》 EI CAS 2010年第3期235-238,共4页
In electroencephalogram (EEG) modeling techniques, data segment selection is the first and still an important step. The influence of a set of data-segment-related parameters on feature extraction and classification in... In electroencephalogram (EEG) modeling techniques, data segment selection is the first and still an important step. The influence of a set of data-segment-related parameters on feature extraction and classification in an EEG-based brain-computer interface (BCI) was studied. An auto search algorithm was developed to study four datasegment-related parameters in each trial of 12 subjects’ EEG. The length of data segment (LDS), the start position of data (SPD) segment, AR order, and number of trials (NT) were used to build the model. The study showed that, compared with the classification ratio (CR) without parameter selection, the CR was increased by 20% to 30% with proper selection of these data-segment-related parameters, and the optimum parameter values were subject-dependent. This suggests that the data-segment-related parameters should be individualized when building models for BCI. 展开更多
关键词 data segment parameter selection EEG classification brain-computer interface （BCI）
暂未订购 下载PDF
Numerical estimation of choice of the regularization parameter for NMR T2 inversion 认领 引用 被引量：5
13
作者 You-Long Zou Ran-Hong Xie Alon Arad 《Petroleum Science》 SCIE CAS CSCD 2016年第2期237-246,共10页
Nuclear Magnetic inversion is the basis of NMR Resonance （NMR） T2 logging interpretation. The regularization parameter selection of the penalty term directly influences the NMR T2 inversion result. We implemented bo... Nuclear Magnetic inversion is the basis of NMR Resonance （NMR） T2 logging interpretation. The regularization parameter selection of the penalty term directly influences the NMR T2 inversion result. We implemented both norm smoothing and curvature smoothing methods for NMR T2 inversion, and compared the inversion results with respect to the optimal regular- ization parameters （（Xopt） which were selected by the dis- crepancy principle （DP）, generalized cross-validation （GCV）, S-curve, L-curve, and the slope of L-curve methods, respectively. The numerical results indicate that the DP method can lead to an oscillating or oversmoothed solution which is caused by an inaccurately estimated noise level. The （Xopt selected by the L-curve method is occa- sionally small or large which causes an undersmoothed or oversmoothed T2 distribution. The inversion results from GCV, S-curve and the slope of L-curve methods show satisfying inversion results. The slope of the L-curve method with less computation is more suitable for NMR T2 inversion. The inverted T2 distribution from norm smoothing is better than that from curvature smoothing when the noise level is high. 展开更多
关键词 NMR T2 inversion Tikhonov regularizationVariable substitution Levenberg-Marquardt method Regularization parameter selection
暂未订购 下载PDF
Parameter selecting and quality predicting of spot welding based on artificial neural networks 认领 引用 被引量：1
14
作者 赵熹华 王宸煜 张若冰 《China Welding》 EI CAS 1998年第2期4-8,共5页
This paper proposes a procedure for using artificial neural networks (ANN) in spot welding , and establishes spot welding parameter selecting ANN systems and spot welding joint quality predicting ANN systems . It has ... This paper proposes a procedure for using artificial neural networks (ANN) in spot welding , and establishes spot welding parameter selecting ANN systems and spot welding joint quality predicting ANN systems . It has been proved that the ANN systems have high prediction precision , providing a new way of parameter selecting and quality predicting in spot welding . 展开更多
关键词 artificial neural networks resistance spot welding parameter selecting quality predicting
暂未订购 下载PDF
Dendritic tip selection during solidification of alloys:Insights from phase-field simulations 认领 引用
15
作者 Qingjie Zhang Hui Xing +1 位作者 Lingjie Wang Wei Zhai 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第9期467-472,共6页
The effect of undercooling DT and the interface energy anisotropy parameter e4 on the shape of the equiaxed dendritic tip has been investigated by using a quantitative phase-field model for solidification of binary al... The effect of undercooling DT and the interface energy anisotropy parameter e4 on the shape of the equiaxed dendritic tip has been investigated by using a quantitative phase-field model for solidification of binary alloys.It was found that the tip radius r increases and the tip shape amplitude coefficient A4 decreases with the increase of the fitting range for all cases.The dendrite tip shape selection parameter sdecreases and then stabilizes with the increase of the fitting range,and sincreases with the increase of e4.The relationship between sand e4 follows a power-law function sµea 4,and a is independent of DT but dependent on the fitting range.Numerical results demonstrate that the predicted sis consistent with the curve of microscopic solvability theory(MST)for e4<0.02,and sobtained from our phase-field simulations is sensitive to the undercooling when e4 is fixed. 展开更多
关键词 phase-field simulations dendritic structure interface energy anisotropy tip shape selection parameter
暂未订购 下载PDF
Transcutaneous electrical acupoint stimulation(TEAS):Applications and challenges 认领 引用 被引量：4
16
作者 Wen-lai ZHOU Jing LI +4 位作者 Xiao-ning SHEN Xia-tong HUA Jing XIE Yan-li ZHOU Lu ZHU 《World Journal of Acupuncture-Moxibustion》 CAS CSCD 2025年第1期10-16,共7页
Transcutaneous electrical acupoint stimulation(TEAS)is a kind of physical therapy that use electric cur-rent through the electrodes placed on the surface of acupoints to produce clinical effects in the human body,whic... Transcutaneous electrical acupoint stimulation(TEAS)is a kind of physical therapy that use electric cur-rent through the electrodes placed on the surface of acupoints to produce clinical effects in the human body,which is characterized by less adverse reaction and convenient operation.It has been widely used in the treatment of various diseases.This review introduces six major clinical applications of TEAS,named analgesia,regulation of gastrointestinal function,improvement of reproductive function,enhancement of cognitive function,promotion of limb function recovery and relief of fatigue.Besides,TEAS has been ap-plied to the treatment of other chronic diseases such as hypertension and diabetes,achieving satisfactory clinical effects.However,two crucial challenges are encountered in the development of TEAS.One is the lack of standardization in the selection of parameters such as waveform,frequency,intensity and stimula-tion duration.The other is the limitation on the flexibility in the acupoint selection.This review analyzes key issues that need to be addressed in the current clinical application of TEAS,such as the selection of parameters and acupoints,and this review provides a certain reference value for optimizing regimens of TEAS and promoting its development and application. 展开更多
关键词 Transcutaneous electrical acupoint stimulation(TEAS) Clinical application Influence factors Parameter selection
暂未订购 下载PDF
DataColor: unveiling biological data relationships through distinctive color mapping 认领 引用 被引量：5
17
作者 Shuang He Wei Dong +8 位作者 Junhao Chen Junyu Zhang Weiwei Lin Shuting Yang Dong Xu Yuhan Zhou Benben Miao Wenquan Wang Fei Chen 《Horticulture Research》 SCIE CSCD 2024年第2期48-58,共11页
In the era of rapid advancements in high-throughput omics technologies,the visualization of diverse data types with varying orders of magnitude presents a pressing challenge.To bridge this gap,we introduce DataColor,a... In the era of rapid advancements in high-throughput omics technologies,the visualization of diverse data types with varying orders of magnitude presents a pressing challenge.To bridge this gap,we introduce DataColor,an all-encompassing software solution meticulously crafted to address this challenge.Our aim is to empower users with the ability to handle a wide array of data types through an assortment of tools,while simultaneously streamlining parameter selection for rapid insights and detailed enhancements.DataColor stands as a robust toolkit,encompassing 23 distinct tools coupled with over 600 parameters.The defining characteristic of this toolkit is its adept utilization of the color spectrum,allowing for the representation of data spanning diverse types and magnitudes.Through the integration of advanced algorithms encompassing data clustering,normalization,squarified layouts,and customizable parameters,DataColor unveils an abundance of insights that lay hidden within the intricate relationships embedded in the data.Whether you find yourself navigating the analysis of expansive datasets or embarking on the quest to visualize intricate patterns,DataColor stands as the comprehensive and potent solution. 展开更多
关键词 handle wide array data types streamlining parameter selection biological data high throughput omics color mapping empower users data clustering visualization diverse data types
暂未订购 下载PDF
Extrapolated Tikhonov method and inversion of 3D density images of gravity data 认领 引用 被引量：2
18
作者 王祝文 许石 +1 位作者 刘银萍 刘菁华 《Applied Geophysics》 SCIE CSCD 2014年第2期139-148,252,共10页
Tikhonov regularization（TR） method has played a very important role in the gravity data and magnetic data process. In this paper, the Tikhonov regularization method with respect to the inversion of gravity data is d... Tikhonov regularization（TR） method has played a very important role in the gravity data and magnetic data process. In this paper, the Tikhonov regularization method with respect to the inversion of gravity data is discussed. and the extrapolated TR method（EXTR） is introduced to improve the fitting error. Furthermore, the effect of the parameters in the EXTR method on the fitting error, number of iterations, and inversion results are discussed in details. The computation results using a synthetic model with the same and different densities indicated that. compared with the TR method, the EXTR method not only achieves the a priori fitting error level set by the interpreter but also increases the fitting precision, although it increases the computation time and number of iterations. And the EXTR inversion results are more compact than the TR inversion results, which are more divergent. The range of the inversion data is closer to the default range of the model parameters, and the model features and default model density distribution agree well. 展开更多
关键词 Gravity data inversion 3D inversion extrapolated Tikhonov regularization method extrapolated Tikhonov parameter selection
暂未订购 下载PDF
Two-dimensional NMR inversion based on fast norm smoothing method 认领 引用 被引量：1
19
作者 Youlong Zou Jun Li +3 位作者 Song Hu Junlei Su Mi Liu Jun Zhang 《Energy Geoscience》 2022年第1期23-34,共12页
Two-dimensional(2D)nuclear magnetic resonance(NMR)inversion operates with massive echo train data and is an ill-posed problem.It is very important to select a suitable inversion method for the 2D NMR data processing.I... Two-dimensional(2D)nuclear magnetic resonance(NMR)inversion operates with massive echo train data and is an ill-posed problem.It is very important to select a suitable inversion method for the 2D NMR data processing.In this study,we propose a fast,robust,and effective method for 2D NMR inversion that improves the computational efficiency of the inversion process by avoiding estimation of some unneeded regularization parameters.Firstly,a method that combines window averaging(WA)and singular value decomposition(SVD)is used to compress the echo train data and obtain the singular values of the kernel matrix.Subsequently,an optimum regularization parameter in a fast manner using the signal-to-noise ratio(SNR)of the echo train data and the maximum singular value of the kernel matrix are determined.Finally,we use the Butler-Reeds-Dawson(BRD)method and the selected optimum regularization parameter to invert the compressed data to achieve a fast 2D NMR inversion.The numerical simulation results indicate that the proposed method not only achieves satisfactory 2D NMR spectra rapidly from the echo train data of different SNRs but also is insensitive to the number of the final compressed data points. 展开更多
关键词 2D NMR inversion Norm smoothing Fast regularization parameter selection
暂未订购 下载PDF
A modeling method of microburst based on multiple vortex ring 认领 引用
20
作者 林连雷 闫芳 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2012年第6期111-114,共4页
Microburst is a special kind of low-level wind shear, which may do great damage to aircrafts. Modelling of a microburst is significant for flight simulations. In this paper we adopt multiple vortex ring principle to m... Microburst is a special kind of low-level wind shear, which may do great damage to aircrafts. Modelling of a microburst is significant for flight simulations. In this paper we adopt multiple vortex ring principle to model microburst and propose a new parameter selection method of multiple vortex ring model. We treat the parameters selection as an optimization problem, and introduce the differential evolution algorithm into it. A nested differential evolution algorithm is proposed to complete the two optimization process, objective optimization and intermediate optimization. The simulation results show that this method can flexibly generate microburst with any maximum wind velocity. 展开更多
关键词 microburst multiple vortex ring parameter selection nested differential evolution
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈