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21,296篇文章
< 1 2 … 250 >
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：
An iterative regularized inversion method of fracture width and height using cross-well optical fiber strain 认领 引用
1
作者 CHEN Ming WANG Ziang +2 位作者 GUO Tiankui LIU Yongzan CHEN Zuorong 《Petroleum Exploration and Development》 SCIE 2026年第1期235-248,共14页
The forward model of optical fiber strain induced by fractures,together with the associated model resolution matrix,is used to demonstrate the interpretability of fracture parameters once the fracture intersects the f... The forward model of optical fiber strain induced by fractures,together with the associated model resolution matrix,is used to demonstrate the interpretability of fracture parameters once the fracture intersects the fiber.A regularized inversion framework for fracture parameters is established to evaluate the influence of measured data quality on the accuracy of iterative regularized inversion.An interpretation approach for both fracture width and height is proposed,and the synthetic forward data with measurement error and field examples are employed to validate the accuracy of the simultaneous inversion of fracture width and height.The results indicate that,after the fracture contacts the fiber,the strain response is strongly sensitive only to the fracture parameters at the intersection location,whereas the interpretability of parameters at other locations remains limited.The iterative regularized inversion method effectively suppresses the impact of measurement error and exhibits high computational efficiency,showing clear advantages for inversion applications.When incorporating the first-order regularization with a Neumann boundary constraint on the tip width,the inverted fracture-width distribution becomes highly sensitive to fracture height;thus,combined with a bisection strategy,simultaneous inversion of fracture width and height can be achieved.Examination using the model resolution matrix,noisy synthetic data,and field data confirms that the iterative regularized inversion model for fracture width and height provides high interpretive accuracy and can be applied to the calculation and analysis of fracture width,fracture height,net pressure and other parameters. 展开更多
关键词 optical fiber strain fracture diagnosis forward model model resolution iterative regularized inversion computational efficiency fracture parameter interpretation
暂未订购 下载PDF
Modeling Bacterial Flow Field with Regularized Singularities 认领 引用
2
作者 Yaochen Yang Daiki Matsunaga +1 位作者 Da Wei Fanlong Meng 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第5期395-413,共19页
The flow field generated by a swimming bacterium serves as a fundamental building block for understanding hydrodynamic interactions between bacteria.Although the flow field generated by a force dipole(stresslet)well c... The flow field generated by a swimming bacterium serves as a fundamental building block for understanding hydrodynamic interactions between bacteria.Although the flow field generated by a force dipole(stresslet)well captures the fluid motion in the far field limit,the stresslet description does not work in the near-field limit,which can be important in microswimmer interactions.Here we propose the model combining an anisotropically regularized stresslet with an isotropically regularized source dipole,and it nicely reproduces the flow field around a swimming bacterium,which is validated by the experimental measurements of the flow field around E.coli and our boundary-element-method simulations of a helical microswimmer,in both cases of the free space and the confined space with a no-slip wall.This work provides a practical tool for obtaining the flow field of the bacterium,and can be utilised to study the collective responses of bacteria in dense suspensions. 展开更多
关键词 microswimmer interactionshere bacterial flow field hydrodynamic interactions swimming bacterium fluid motion isotropically regularized source dipoleand flow field anisotropically regularized stresslet
暂未订购 下载PDF
Multiparameter Bayesian full-waveform inversion with uncertainty quantification based on regularized inverse scattering theory for elastic transversely isotropic media 认领 引用
3
作者 Wen-Rui Ye Xing-Guo Huang 《Petroleum Science》 SCIE EI CAS CSCD 2026年第6期3180-3212,共33页
Complex subsurface structures exhibit significant anisotropic characteristics,making multi-parameter imaging techniques important for achieving a more comprehensive geological interpretation.Fullwaveform inversion(FWI... Complex subsurface structures exhibit significant anisotropic characteristics,making multi-parameter imaging techniques important for achieving a more comprehensive geological interpretation.Fullwaveform inversion(FWI)as a state-of-the-art method for reconstructing subsurface properties based on seismic wavefield modeling and data misfit minimization has been widely applied to isotropic media in both synthetic and field datasets.However,challenges such as crosstalk correlation and inaccuracy of the initial model indicate that further advancements are required to enhance resolution and computational efficiency.We propose an elastic FWI in the frequency domain for two-dimensional(2D)TI media to characterize their physical properties appropriately,as they are common in sedimentary basin environments.Different from traditional inversion schemes,our approach is formulated based on Bayesian inference,which automatically facilitates uncertainty analysis of the inversion results.Seismic data are acquired via the integral equation(IE)method grounded in scattering theory,where the sensitivity kernel is explicitly constructed using Green's functions,hence facilitating the calculation of gradient and Hessian.A Krylov subspace iterative method provides the approximated solution of the Lippmann-Schwinger(L-S)equation without sacrificing the accuracy.Furthermore,we incorporate the minimum support(MS)stabilizing functional as a model misfit term to regularize the objective function.A randomized singular value decomposition(SVD)approach is used to approximate and decompose the prior preconditioned Hessian.Both the model and covariance are updated through the iterative extended Kalman filter(IEKF)that implemented in the form of the Levenberg-Marquardt(LM)algorithm,thereby enabling practical uncertainty quantification.Numerical tests are conducted on two synthetic TI models with vertical and tilted symmetry axes,respectively,illustrating the precision and robustness of our method. 展开更多
关键词 Inverse scattering theory Full waveform inversion Anisotropy Multi-parameter inversion Uncertainty quantification Regularization term Randomized singular value decomposition
暂未订购 下载PDF
Sobolev space norm regularized full waveform inversion for ultrasound computed tomography 认领 引用 被引量：1
4
作者 Panpan Li Yubing Li +2 位作者 Chang Su Zeyuan Dong Weijun Lin 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第5期444-456,共13页
Full waveform inversion(FWI)is a complex data fitting process based on full wavefield modeling,aiming to quantitatively reconstruct unknown model parameters from partial waveform data with high-resolution.However,this... Full waveform inversion(FWI)is a complex data fitting process based on full wavefield modeling,aiming to quantitatively reconstruct unknown model parameters from partial waveform data with high-resolution.However,this process is highly nonlinear and ill-posed,therefore achieving high-resolution imaging of complex biological tissues within a limited number of iterations remains challenging.We propose a multiscale frequency–domain full waveform inversion(FDFWI)framework for ultrasound computed tomography(USCT)imaging of biological tissues,which innovatively incorporates Sobolev space norm regularization for enhancement of prior information.Specifically,we investigate the effect of different types of hyperparameter on the imaging quality,during which the regularization weight is dynamically adapted based on the ratio of the regularization term to the data fidelity term.This strategy reduces reliance on predefined hyperparameters,ensuring robust inversion performance.The inversion results from both numerical and experimental tests(i.e.,numerical breast,thigh,and ex vivo pork-belly tissue)demonstrate the effectiveness of our regularized FWI strategy.These findings will contribute to the application of the FWI technique in quantitative imaging based on USCT and make USCT possible to be another high-resolution imaging method after x-ray computed tomography and magnetic resonance imaging. 展开更多
关键词 full waveform inversion Sobolev space norm regularization ultrasound computed tomography
暂未订购 下载PDF
HerbGL:a network propagation and graph regularization-based framework for herb pairs prediction in traditional Chinese medicine 认领 引用
5
作者 Weixiang Liu Qian Yuan +3 位作者 Junjie Zhang Xinliang Sun Kongfa Hu Tao Yang 《Digital Chinese Medicine》 CAS CSCD 2026年第2期265-277,共13页
Objective To address the challenges of systematically identifying herb pairs in traditional Chinese medicine(TCM),we proposed HerbGL,a framework for predicting potential herb pairs that integrates network propagation ... Objective To address the challenges of systematically identifying herb pairs in traditional Chinese medicine(TCM),we proposed HerbGL,a framework for predicting potential herb pairs that integrates network propagation and graph regularization.Methods Based on the assumption that herbal actions induce subtle perturbations in biological systems,a framework named HerbGL was proposed.Random walk with restart(RWR)was first applied to the protein-protein interaction(PPI)network to reconstruct herb-specific perturbation effects and generate weighted subnetworks.Then,to quantify affinity between herb pairs,two network-proximity metrics,Closeness and PageRank,were computed from the weighted subnetworks to construct herb-pair affinity matrices.Finally,these matrices,together with known herb pairs(derived from co-occurrence analysis of TCM formulas with a threshold determined from the inflection point of the frequency distribution),were incorporated into a graph regularization model to predict potential herb pairs.Model performance was assessed through baseline comparison,ablation and robustness experiment under different ratios of positive and negative samples,using the area under the receiver operating characteristic curve(AUROC),the area under the precision-recall curve(AUPRC),accuracy,and precision as evaluation metrics.Furthermore,the predicted herb pairs were validated through both literature evidence and Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses.Results The weighted subnetworks constructed by RWR provided a refined simulation of herb-specific perturbation effects,which formed the basis for subsequent affinity modeling and prediction.Analysis of herb pair co-occurrence frequencies revealed a marked change around 150,which was selected as the threshold to distinguish herb pairs from non-herb pairs.HerbGL exhibited superior predictive performance compared with baseline models(AUROC=0.9705,AUPRC=0.9555,accuracy=0.7266,precision=0.9706).Ablation results showed that removing the Closeness and PageRank metrics substantially degraded performance(AUROC=0.8191,AUPRC=0.8768),confirming their necessity.Robustness evaluation under an imbalanced positive-to-negative sample ratio of 1:5 yielded AUROC=0.9696 and AUPRC=0.8404,indicating stable predictive ability.Moreover,multiple case studies further validated the rationality of the predicted herb pairs,such as Fangfeng(Saposhnikoviae Radix)and Qingpi(Citri Reticulatae Pericarpium Viride)which are recorded in Liangpeng Huiji(《良朋汇集》,Collection of Excellent Recipes)Vol.3:Fangfeng Shengma Tang(防风升麻汤).Additionally,pathway enrichment analysis of the Renshen(Ginseng Radix et Rhizoma)and Lianqiao(Forsythiae Fructus)pair further supported the biological plausibility of their compatibility.Conclusion HerbGL offers an effective and biologically informed framework for identifying herb pairs in TCM.Beyond improving herb pair prediction,the framework also provides data support for research on herb compounds and mechanisms,thereby supporting data-driven exploration of TCM compatibility. 展开更多
关键词 Traditional Chinese medicine Herb pair Network propagation Graph regularization Network pharmacology
暂未订购 下载PDF
Phase-based polarized direct envelope inversion with total variation regularization for simultaneous source seismic data:Application to SEG 2014 Chevron blind test dataset 认领 引用
6
作者 Yong Hu Xi-Zhu Guan +2 位作者 Li-Yun Fu Yi-Bo Wang Ru-Shan Wu 《Petroleum Science》 SCIE EI CAS CSCD 2026年第6期3248-3269,共22页
In subsalt hydrocarbon exploration,the strong velocity contrast associated with salt structures poses significant challenges to conventional full waveform inversion(FWI)method.While direct envelope inversion can inver... In subsalt hydrocarbon exploration,the strong velocity contrast associated with salt structures poses significant challenges to conventional full waveform inversion(FWI)method.While direct envelope inversion can invert large-scale salt dome,it fails to invert the salt-bottom velocity structures due to the absence of waveform phase information.To solve this problem,we first use a sliding Gaussian window to decompose seismic data into the local scale waveform.Subsequently,we combine the local scale envelope signal with waveform instantaneous phase to obtain the polarity envelope.The resulting polarity envelope can invert low-frequency components while preserving the phase characteristics of seismic data,enabling more accurate low-wavenumber velocity structures.Based on this,we propose a phase-based polarized direct envelope inversion with total variation regularization for simultaneous source seismic data(simultaneous source TV-PDEI)to improve the accuracy of velocity inversion,remove the crosstalk noise,and enhance the computational efficiency.Numerical experiments on salt models and Chevron blind dataset test demonstrate that the simultaneous source TV-PDEI efficiently provides a robust initial velocity model for FWI. 展开更多
关键词 Full waveform inversion Direct envelope inversion Polarity envelope Chevron blind dataset test Total variation regularization
暂未订购 下载PDF
Offline Generalized Actor-Critic With Distance Regularization 认领 引用
7
作者 Huanting Feng Yuhu Cheng Xuesong Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第1期57-71,共15页
In order to address the issue of overly conservative offline reinforcement learning(RL) methods that limit the generalization of policy in the out-of-distribution(OOD) region,this article designs a surrogate target fo... In order to address the issue of overly conservative offline reinforcement learning(RL) methods that limit the generalization of policy in the out-of-distribution(OOD) region,this article designs a surrogate target for OOD value function based on dataset distance and proposes a novel generalized Q-learning mechanism with distance regularization(GQDR).In theory,we not only prove the convergence of GQDR,but also ensure that the difference between the Q-value learned by GQDR and its true value is bounded.Furthermore,an offline generalized actor-critic method with distance regularization(OGACDR) is proposed by combining GQDR with actor-critic learning framework.Two implementations of OGACDR,OGACDR-EXP and OGACDRSQR,are introduced according to exponential(EXP) and opensquare(SQR) distance weight functions,and it has been theoretically proved that OGACDR provides a safe policy improvement.Experimental results on Gym-MuJoCo continuous control tasks show that OGACDR can not only alleviate the overestimation and overconservatism of Q-value function,but also outperform conservative offline RL baselines. 展开更多
关键词 Actor-critic distance regularization generalized Qlearning offline reinforcement learning out-of-distribution(OOD)
暂未订购 下载PDF
Federated Multi-Label Feature Selection via Dual-Layer Hybrid Breeding Cooperative Particle Swarm Optimization with Manifold and Sparsity Regularization 认领 引用
8
作者 Songsong Zhang Huazhong Jin +5 位作者 Zhiwei Ye Jia Yang Jixin Zhang Dongfang Wu Xiao Zheng Dingfeng Song 《Computers, Materials & Continua》 SCIE EI 2026年第1期1141-1159,共19页
Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant chal... Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics. 展开更多
关键词 Multi-label feature selection federated learning manifold regularization sparse constraints hybrid breeding optimization algorithm particle swarm optimizatio algorithm privacy protection
暂未订购 下载PDF
GLOBAL REGULARITY FOR THE 2D MICROPOLAR RAYLEIGH-BENARD CONVECTION SYSTEM WITH VELOCITY CRITICAL DISSIPATION,LOWER MICRO-ROTATIONAL DISSIPATION AND NO TEMPERATURE DIFFUSION 认领 引用
9
作者 Baoquan YUAN Changhao LI 《Acta Mathematica Scientia》 SCIE CSCD 2026年第3期1405-1425,共21页
This paper studies the global regularity problem for the 2D micropolar Rayleigh-Bénard convection system with velocity critical(-Δ)1/2dissipation,micro-rotation velocity fractional(-Δ)5/6dissipation witho... This paper studies the global regularity problem for the 2D micropolar Rayleigh-Bénard convection system with velocity critical(-Δ)1/2dissipation,micro-rotation velocity fractional(-Δ)5/6dissipation without temperature diffusion.By introducing three combined quantities,using the technique of Littlewood-Paley decomposition,and with the help of the Besov space,we establish the global regularity result of strong solutions to this system in the Sobolev space Hs(R2)for s≥2. 展开更多
关键词 micropolar fliud Rayleigh-Bénard convection global regularity Littlewood-Paley theory
暂未订购 下载PDF
Enhancing Adversarial Example Transferability via Regularized Constrained Feature Layer 认领 引用
10
作者 Xiaoyin Yi Long Chen +2 位作者 Jiacheng Huang Ning Yu Qian Huang 《Computers, Materials & Continua》 SCIE EI 2025年第4期157-175,共19页
Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they re... Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques. 展开更多
关键词 Adversarial examples black-box transferability regularized constrained transfer-based adversarial attacks
暂未订购 下载PDF
Generalized uncertainty principle from the regularized self-energy 认领 引用
11
作者 Kimet Jusufi Ahmed Farag Ali 《Communications in Theoretical Physics》 SCIE CAS CSCD 2025年第1期92-100,共9页
We use the Schrödinger–Newton equation to calculate the regularized self-energy of a particle using a regular self-gravitational and electrostatic potential derived in string T-duality.The particle mass M is no ... We use the Schrödinger–Newton equation to calculate the regularized self-energy of a particle using a regular self-gravitational and electrostatic potential derived in string T-duality.The particle mass M is no longer concentrated into a point but is diluted and described by a quantum-corrected smeared energy density resulting in corrections to the energy of the particle,which is interpreted as a regularized self-energy.We extend our results and find corrections to the relativistic particles using the Klein–Gordon,Proca and Dirac equations.An important finding is that we extract a form of the generalized uncertainty principle(GUP)from the corrected energy.This form of the GUP is shown to depend on the nature of particles;namely,for bosons(spin 0 and spin 1)we obtain a quadratic form of the GUP,while for fermions(spin 1/2)we obtain a linear form.The correlation we find between spin and GUP may offer insights for investigating quantum gravity. 展开更多
关键词 generalized uncertainty principle T-duality regularized self-energy
暂未订购 下载PDF
SOME NEW REGULARITY CRITERIA OF THE INCOMPRESSIBLE 3D MHD EQUATIONS 认领 引用
12
作者 Honglin ZHANG Li LI Qingning ZHANG 《Acta Mathematica Scientia》 SCIE CSCD 2026年第3期1340-1357,共18页
In this paper,we investigate several regularity criteria to the 3D incompressible magnetohydrodynamic equations.These criteria are based on certain assumptions made in partial elements of the velocity gradient tensor ... In this paper,we investigate several regularity criteria to the 3D incompressible magnetohydrodynamic equations.These criteria are based on certain assumptions made in partial elements of the velocity gradient tensor and pressure,respectively.By making use of the Littlewood-Paley decomposition,we show that the solution(u,b)can be smoothly extended after time T if any two groups of functions(∂1u1,∂1b1),(∂2u2,∂2b2)and(∂3u3,∂3b3belong to the space L1(0,T;B∞,∞). 展开更多
关键词 magnetohydrodynamic equations Navier-Stokes equations regularity criteria Besov space Littlewood-Paley decomposition
暂未订购 下载PDF
Gradient Descent with Time-Decaying Regularization for Training Linear Neural Networks 认领 引用
13
作者 Sergio Isai Palomino-Resendiz César Ulises Solís-Cervantes +2 位作者 Luis Alberto Cantera-Cantera Jorge de Jesús Morales-Mercado Diego Alonso Flores-Hernández 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期766-782,共17页
Many linear-in-parameters models arising in identification and control can be expressed as singlelayer artificial neural networks(ANNs)with linear activation,enabling online learning viafirst-order optimization.In pra... Many linear-in-parameters models arising in identification and control can be expressed as singlelayer artificial neural networks(ANNs)with linear activation,enabling online learning viafirst-order optimization.In practice,however,standard gradient descent ofien exhibits slow convergence,large intermediate weights,and stagnation when the regressor data are ill-conditioned or computations are performed underfinite precision.This paper proposes Gradient Descent with Time-Decaying Regularization(GD-TDR),a training algorithm that augments the quadratic loss with a regularization term whose weight decays exponentially in time.fie proposed schedule enforces uniform strong convexity during early iterations,efiectively mitigating neural-paralysis-like behavior associated withfiat directions,while asymptotically vanishing so that the unregularized least-squares solution is recovered.A convergence theorem for GD-TDR is established and a concise pseudocode implementation is provided.Numerical and embedded experiments on an online identification problem of a Chua-type chaotic oscillator demonstrate that GD-TDR converges faster and avoids stagnation compared to standard gradient descent,without introducing the steady-state bias characteristic offixed quadratic regularization. 展开更多
关键词 Time-decaying regularization gradient descent single-layer linear neural network online system identification chaotic oscillator embedded implementation
暂未订购 下载PDF
Compression behavior of a cell of a tetrachiral metamaterial with regular and irregular structure 认领 引用
14
作者 Linar Akhmetshin Kristina Iokhim Alexander Eremin 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第5期267-275,共9页
Metamaterials are materials whose unique properties are associated with their geometric structure rather than the chemical composition of the base material.These properties can be influenced at various scales but this... Metamaterials are materials whose unique properties are associated with their geometric structure rather than the chemical composition of the base material.These properties can be influenced at various scales but this work focuses on a cell’s topological defect.Samples for mechanical testing were printed using digital light processing lithography technology.One of the characteristics studied in this work is the rotation of the cell’s face under uniaxial loading.For both the regular cell and the cell with topological defect,the rotation was directed clockwise,which corresponds to the direction of twisting of the structures on the lateral faces.The maximum twisting angle of the regular cell is 0.84°.The introduction of topological defect reduced the twist angle of the cell by more than 30%.It was found that the force value in the cell with a topological defect is higher,indicating that the cell with the defect is more rigid than the cell without it. 展开更多
关键词 Mechanical metamaterial Chirality Twist of the sample Rotation of the structure Regular structure Topological defect Stiffness
暂未订购 下载PDF
EXISTENCE AND DEGENERATE REGULARITY OF THE TRAJECTORY STATISTICAL SOLUTION FOR THE 3D BOUSSINESQ EQU ATIONS WITH DAMPING 认领 引用
15
作者 Yuming QIN Huite JIANG 《Acta Mathematica Scientia》 SCIE CSCD 2026年第3期1324-1339,共16页
In this paper,we investigate the existence and degenerate regularity of trajectory statistical solutions for the three-dimensional Boussinesq system with damping.We first establish that the existence of trajectory att... In this paper,we investigate the existence and degenerate regularity of trajectory statistical solutions for the three-dimensional Boussinesq system with damping.We first establish that the existence of trajectory attractor holds,then we use it and natural translation semigroup to construct the trajectory statistical solutions in the trajectory space.Furthermore,we demonstrate that when the Grashof number related to the system remains sufficiently small,the trajectory statistical solution exhibits degenerate regularity. 展开更多
关键词 Boussinesq equations trajectory statistical solution trajectory attractor degenerate regularity
暂未订购 下载PDF
A regularization technique for accurate reconstruction of numerical solution of wave propagation problems 认领 引用
16
作者 Salvatore Lopez 《Theoretical & Applied Mechanics Letters》 EI CAS CSCD 2026年第3期39-50,共12页
In the numerical solution of wave propagation problems,spurious oscillations occur in the exact time integration of the related equation of motion.This is due to the high frequencies introduced by the spatial discreti... In the numerical solution of wave propagation problems,spurious oscillations occur in the exact time integration of the related equation of motion.This is due to the high frequencies introduced by the spatial discretization,given the small size of the mesh elements and the integration step required to capture the wave phenomena.Currently,an answer to this problem is given by the use of the smoothing properties,intrinsic to the scheme or obtained through artificial viscosity,of dissipative time integration methods.More recently,in an alternative approach to the problem,the solution has been regularized via a post processing smoothing technique.In particular,on the basis of an initial nondissipative scheme,at a fixed observation time a series of steps of an appropriate dissipative time integration method achieves the desired smoothing.However,in both approaches,as the dissipative steps are performed,the noise progressively decreases,but the important values related to the peak regions of the solution degrade significantly.Here we describe a regularization process that automatically returns a solution where the noise has been eliminated but does not affect the significant regions of the solution.The presented technique recognizes the flat or peak shapes of the original solution among the oscillating components representing the noise.Operationally,the presented algorithm,starting from a nondissipative stepby-step scheme for time integration,iteratively smooths the related kinematic quantities and finally recovers the regularized solution as a suitable composition of smoothed and unsmoothed subdomains. 展开更多
关键词 Regularization technique Numerical smoothing filters Time integration Wave propagation
暂未订购 下载PDF
Suitable Weak Solutions and Partial Regularity for Simplified Magneto-Viscoelastic Flows 认领 引用
17
作者 Liu Qiao Zuo Zhongbao 《数学理论与应用》 2026年第2期40-67,共28页
In this paper,inspired by the celebrated work of Caffarelli et al.[2]on partial regularity for the classic incompressible Navier-Stokes system and by Du et al.[4]on suitable weak solutions for the co-rotational Beris-... In this paper,inspired by the celebrated work of Caffarelli et al.[2]on partial regularity for the classic incompressible Navier-Stokes system and by Du et al.[4]on suitable weak solutions for the co-rotational Beris-Edwards system,we establish the global existence of suitable weak solutions to a simplified magneto-viscoelastic flow system in three-dimensional space.This model couples the incompressible Navier-Stokes equations for the fluid velocity field,an evolution equation for the deformation tensor,and a gradient flow equation for the magnetization vector.Furthermore,we prove that the one-dimensional space-time Hausdorff measure of the potential singular set of such suitable weak solutions is zero. 展开更多
关键词 Suitable weak solution;Partial regularity;Magneto-viscoelastic flow;Hausdorff dimension
暂未订购 下载PDF
Regularized least-squares migration of simultaneous-source seismic data with adaptive singular spectrum analysis 认领 引用 被引量：14
18
作者 Chuang Li Jian-Ping Huang +1 位作者 Zhen-Chun Li Rong-Rong Wang 《Petroleum Science》 SCIE CAS CSCD 2017年第1期61-74,共14页
Simultaneous-source acquisition has been recog- nized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of... Simultaneous-source acquisition has been recog- nized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of adjacent sources. To overcome this problem, we propose the regularized least-squares reverse time migration method （RLSRTM） using the singular spectrum analysis technique that imposes sparseness constraints on the inverted model. Additionally, the difference spectrum theory of singular values is presented so that RLSRTM can be implemented adaptively to eliminate the migration artifacts. With numerical tests on a fiat layer model and a Marmousi model, we validate the superior imaging quality, efficiency and convergence of RLSRTM compared with LSRTM when dealing with simultaneoussource data, incomplete data and noisy data. 展开更多
关键词 Least-squares migration Adaptive singularspectrum analysis Regularization Blended data
暂未订购 下载PDF
Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data—A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake 认领 引用 被引量：6
19
作者 XU Min ZENG Guang-ming +3 位作者 XU Xin-yi HUANG Guo-he SUN Wei JIANG Xiao-yun 《Journal of Environmental Sciences》 SCIE EI CAS 2005年第6期946-952,共7页
Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of t... Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake. 展开更多
关键词 Dongting Lake chlorophyll-a Bayesian regularized BP neural network model sum of square weights
暂未订购 下载PDF
Two-dimensional regularized inversion of AMT data based on rotation invariant of Central impedance tensor 认领 引用 被引量：5
20
作者 XiaoZhong Tong JianXin Liu AiYong Li 《Earth and Planetary Physics》 CAS 2018年第5期430-437,共8页
Considering the uncertainty of the electrical axis for two-dimensional audo-magnetotelluric(AMT) data processing, an AMT inversion method with the Central impedance tensor was presented. First, we present a calculatio... Considering the uncertainty of the electrical axis for two-dimensional audo-magnetotelluric(AMT) data processing, an AMT inversion method with the Central impedance tensor was presented. First, we present a calculation expression of the Central impedance tensor in AMT, which can be considered as the arithmetic mean of TE-polarization mode and TM-polarization mode in the twodimensional geo-electrical model. Second, a least-squares iterative inversion algorithm is established, based on a smoothnessconstrained model, and an improved L-curve method is adopted to determine the best regularization parameters. We then test the above inversion method with synthetic data and field data. The test results show that this two-dimensional AMT inversion scheme for the responses of Central impedance is effective and can reconstruct reasonable two-dimensional subsurface resistivity structures. We conclude that the Central impedance tensor is a useful tool for two-dimensional inversion of AMT data. 展开更多
关键词 audio-magnetotelluric/AMT impedance tensor rotation invariants two-dimensional geo-electrical model regularized inversion
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 … 250 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈