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Erratum to: Deep learning technique based efficient optimizationmethod for cone dielectric energy generator 认领 引用
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作者 Demin Zhao Aoyu Xiao +4 位作者 Zewen Gu Menghang Chen Guoqiang Xu Bin Zhao Jianlin Liu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第2期142-142,共1页
The name of Bin Zhao in the original published Chinese section is“赵斌”,which should be corrected to“赵彬”.
关键词 deep learning bin zhao cone dielectric energy generator optimization method
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On the Use of the Nelder-Mead Simplex Method in Control Design and Systems Theory 认领 引用
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作者 Laura Menini Corrado Possieri Antonio Tornambe 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第1期186-204,共19页
The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.Furthermore,it is particularly parsim... The Nelder-Mead simplex method is a well-known algorithm enabling the minimization of functions that are not available in closed-form and that need not be differentiable or convex.Furthermore,it is particularly parsimonious on the number of function evaluations,thus making it preferable to convex optimization paradigms in the case,common when dealing with control design problems,that the objective function of the optimization problem is non-differentiable,non-convex,and its closed-form is not available or difficult to be computed analytically.The main goal of this paper is to show how the joint use of the Nelder-Mead simplex method and the Morrison algorithm can be successfully used to solve relevant and challenging control problems that cannot be easily solved using analytic methods.In particular,it is shown how the problems of strong stabilization,static output feedback stabilization,and design of robust controllers having fixed structure can be framed as optimization problems,which,in turn,can be efficiently solved by coupling the two above mentioned algorithms.The performance of this procedure is compared with state-of-the-art techniques on dozens of static output feedback benchmark case studies,and its effectiveness is demonstrated by several examples. 展开更多
关键词 Optimization method robust controller static output feedback strong stabilizability
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Spatially Reconfigurable Antenna Arrays for 6G Networks:Modeling,Methods,and Applications 认领 引用
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作者 Wen Wang Yongming Huang Cheng Zhang 《Journal of Communications and Information Networks》 EI CSCD 2026年第2期170-202,共33页
Spatially reconfigurable antenna arrays(SRAAs)have recently emerged as a promising paradigm for enhancing wireless system performance by treating antenna position and orientation as new spatial degrees of freedom(DoFs... Spatially reconfigurable antenna arrays(SRAAs)have recently emerged as a promising paradigm for enhancing wireless system performance by treating antenna position and orientation as new spatial degrees of freedom(DoFs).Unlike conventional fixed-geometry antenna arrays,SRAAs enable geometry-aware adaptation of the physical aperture,thereby allowing wireless systems to actively exploit spatial channel variations beyond signal-domain processing.This capability is particularly attractive for future sixth-generation(6G)networks that operate in highly dynamic propagation environments and face stringent performance requirements.This review provides a comprehensive and system-oriented overview of SRAAs from both theoretical and practical perspectives.Firstly,we present a unified and geometry-aware channel modeling framework for spatial reconfiguration at different architectural granularities.Secondly,we analyze how position-and orientation-induced channel variations,along with their combined effects,and enable performance gains without relying solely on massive antenna scaling.Afterwards,we survey design and optimization methods for position-orientation reconfiguration,covering both model-and learning-based techniques.Practical considerations are also discussed through a systematic review of hardware implementation options and channel estimation techniques under spatial reconfiguration.To further illustrate the system-level ben-efits of SRAAs,representative applications are examined,including point-to-point and multiuser multiple-input multiple-output(MIMO),cell-free massive MIMO,as well as aerial and mobile communications.A dedicated case study on six-dimensional aerial rotatable antenna(6DARA)-enabled cell-free networks is provided to demonstrate how array-wise position and orientation control,combined with distributed optimization,can achieve substantial performance gains with manageable complexity.Finally,we outline key issues and future directions for the large-scale and practical deployment of SRAAs in 6G wireless networks. 展开更多
关键词 spatially reconfigurable antenna arrays spatial degrees of freedom movable and rotatable antennas multiple-input multiple-output channel modeling and estimation optimization methods hardware implementation sixth-generation networks
AI Model Compression Methods: A Distribution-Aware Residual Entropy Quantization 认领 引用
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作者 Nikita Sakovich Dmitry Aksenov +1 位作者 Ekaterina Pleshakova Sergey Gataullin 《Computers, Materials & Continua》 SCIE EI 2026年第8期854-864,共11页
We introduce the DARE-Q(Distribution-Aware Residual Entropy Quantization)method—a post-training quantization method for neural network weights designed to reduce bit-width with minimal degradation of model quality.Un... We introduce the DARE-Q(Distribution-Aware Residual Entropy Quantization)method—a post-training quantization method for neural network weights designed to reduce bit-width with minimal degradation of model quality.Unlike traditional approaches that solely optimize the mean squared error of weight approximation,DARE-Q additionally considers the entropy of the quantization residual,allowing for control over the statistical properties of the resulting error.The method is based on channel-wise symmetric uniform quantization with scaling based on a combined loss function that includes L2 distortion and entropy regularization.The DARE-Q method is implemented as a compact DAREQuantLinear module which can be easily integrated into standard transformer pipelines without changing the inference logic or using specific kernels.The experimental analysis was conducted on the language models facebook/opt-125m and facebook/opt-350m,which contain approximately 125 and 350 million parameters.The quality of the models was assessed using the standard perplexity metric(PPL)computed on the wikitext-2-raw-v1 dataset.DARE-Q is completely data-free and does not require model retraining or calibration data,which makes it the only viable option in privacy-sensitive or confidential environments where access to the original training data is restricted—precisely the setting where methods such as GPTQ and AWQ cannot be applied.The observed increase in PPL relative to data-dependent baselines reflects this fundamental trade-off rather than a shortcoming of the approach.By leveraging per-channel scale selection and a combined loss function,DARE-Q provides a flexible trade-off between approximation accuracy and quantization error structure,creating an attractive algorithmic basis for further improvement of model compression methods. 展开更多
关键词 Artificial intelligence large language models mathematical optimization methods model compression quantization methods information theory high-performance computing
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Tunnel Micro-deformation Monitoring Method Based on Improved PS-InSAR and Its Geophysical Application Analysis 认领 引用
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作者 Meng-wei Han Gu-hua Pu +9 位作者 Jin-zhuang Wang Zi-heng Gao Xiao-qian Yang Bo Zhang Ba-he Yang Jun Ma Hai-yun Wang Yong-can Chen Xi-can Zhao Wei-jian Liu 《Applied Geophysics》 SCIE CSCD 2026年第1期152-161,429,共10页
Tunnel deformation is a direct manifestation of the stress redistribution of rock and soil masses,and high-precision monitoring of it is an important challenge in the eld of geophysical engineering.This study applies ... Tunnel deformation is a direct manifestation of the stress redistribution of rock and soil masses,and high-precision monitoring of it is an important challenge in the eld of geophysical engineering.This study applies the improved PS-InSAR technology to tunnel deformation monitoring,overcoming the limitations of traditional methods(such as total stations)with limited spatial coverage and poor continuity.Four core innovations enable millimeter-level precision breakthroughs:adaptive quality map fusion of coherence coefficientγand phase derivative variance for dynamic reliable area partitioning;branch-cutting method optimization using residual point clustering and Canny forbidden-zone constraints reduces invalid paths by 40%while suppressing lining joint phase jumps;dynamic weighted least squares(WLS)model integrating weighted coherence with blast disturbance gradient achieves 52%high-frequency noise suppression and precise separation of short-period construction disturbance signals;3D integral correction introduces DEM dynamic calibration projection coefcient k(improving by 30%in curved sections),reducing axial projection error from 15%-30%to<5%.In the Yunnan Amai Tunnel eld test,spatial resolution reaches 0.1m in sensitive zones with deformation inversion error<5%,successfully capturing instantaneous blasting deformation(0.46-0.49mm)and structural trend displacement at the face.The monitoring accuracy is more than three times higher than traditional methods,providing reliable technical support for safety warnings in high-risk sections. 展开更多
关键词 Persistent Scatterer Interferometric Synthetic Aperture Radar(PS-InSAR) Adaptive Quality Map Branch-Cutting Method Optimization Dynamic Weighted Least Squares(WLS)Model 3D Integral Correction Tunnel Deformation Monitoring Geophysical Application
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A high output power 340 GHz balanced frequency doubler designed based on linear optimization method 认领 引用
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作者 LIU Zhi-Cheng ZHOU Jing-Tao +5 位作者 MENG Jin WEI Hao-Miao YANG Cheng-Yue SU Yong-Bo JIN Zhi JIA Rui 《红外与毫米波学报》 SCIE EI CAS CSCD 北大核心 2025年第2期184-191,共8页
In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the ... In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%. 展开更多
关键词 linear optimization method(LOM) three-dimensional electromagnetic model(3D-EM) Harmonic impedance optimization Schottky planar diode Terahertz frequency doubler
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Probabilistic Rock Slope Stability Assessment of Heterogeneous Pyroclastic Slopes Considering Collapse Using Monte Carlo Methodology 认领 引用
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作者 Miguel A.Millán Rubén A.Galindo Fausto Molina-Gómez 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第9期2923-2941,共19页
Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patte... Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making. 展开更多
关键词 Pyroclast Monte Carlo rock slope volcanic rock discontinuity layout optimization method non-homogeneous slope spatial variability
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A New Method to Calculate Nonlinear Optimal Perturbations for Ensemble Forecasting 认领 引用 被引量：3
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作者 Junjie MA Wansuo DUAN +1 位作者 Zhuomin LIU Ye WANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第5期952-967,共16页
Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly effi... Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events. 展开更多
关键词 initial uncertainty conditional nonlinear optimal perturbation optimization method ensemble forecasting
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Flow Ripple Reduction of Axial Piston Pump for Multiple Working Statuses with Fast Structural Optimization Method 认领 引用 被引量：1
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作者 Yuanzhi Xu Renyuan Wang +3 位作者 Ming Deng Zhengyi Gu Yan Xie Zongxia Jiao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第6期562-583,共22页
The flow ripple caused by an axial piston pump may lead to pipe vibrations and lower hydraulic component reliability,which are of particular concern in hydraulic systems.The valve plate of the pump is considered the p... The flow ripple caused by an axial piston pump may lead to pipe vibrations and lower hydraulic component reliability,which are of particular concern in hydraulic systems.The valve plate of the pump is considered the part most related to flow ripple,and its structural design is an important topic.In this study,an analytical model for the axial piston pump flow ripple was established and verified using a numerical analysis with computational fluid dynamics(CFD)calculations.Moreover,a parametric analysis of the valve plate was performed to investigate the critical parameters and their ranges.A fast optimization method,the rotation vector optimization method(RVOM),was proposed for the valve plate design and compared with the currently used optimization methods to prove its efficiency.As a constant-pressure pump works in different states of swashplate angle,outlet pressure,and pump speed,an optimization principle for the entire working status was proposed to achieve the overall reduction performance.A test rig for an aircraft hydraulic pump was established,and validation experiments were conducted.It was determined that the optimized pump could achieve reduction at multiple working statuses,and the largest pressure pulsation reduction ratios for the typical speed and speed sweep tests reached 64.7%and 71.7%,respectively.The model and method proposed in this study are proven to be effective and accurate. 展开更多
关键词 Axial piston pump Optimization method Flow ripple Valve plate design Multiple working statuses
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Methods for enhancing the capacity of electrode materials in low-temperature lithium-ion batteries 认领 引用 被引量：7
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作者 Ying Na Xiaohong Sun +2 位作者 Anran Fan Shu Cai Chunming Zheng 《Chinese Chemical Letters》 SCIE CAS CSCD 2021年第3期973-982,共10页
Lithium-ion batteries(LIBs)have evolved into the mainstream power source of ene rgy sto rage equipment by reason of their advantages such as high energy density,high power,long cycle life and less pollution.With the e... Lithium-ion batteries(LIBs)have evolved into the mainstream power source of ene rgy sto rage equipment by reason of their advantages such as high energy density,high power,long cycle life and less pollution.With the expansion of their applications in deep-sea exploration,aerospace and military equipment,special working conditions have placed higher demands on the low-temperature performance of LIBs.However,at low temperatures,the severe polarization and inferior electrochemical activity of electrode materials cause the acute capacity fading upon cycling,which greatly hindered the further development of LIBs.In this review,we summarize the recent important progress of LIBs in low-temperature operations and introduce the key methods and the related action mechanisms for enhancing the capacity of the various cathode and anode materials.It aims to promote the development of high-performance electrode materials and broaden the application range of LIBs. 展开更多
关键词 Lithium-ion batteries Low-temperature capacity Cathode materials Anode materials Optimizing methods
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Hybrid AI-IoT Framework with Digital Twin Integration for Predictive Urban Infrastructure Management in Smart Cities 认领 引用 被引量：1
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作者 Abdullah Alourani Mehtab Alam +2 位作者 Ashraf Ali Ihtiram Raza Khan Chandra Kanta Samal 《Computers, Materials & Continua》 SCIE EI 2026年第1期462-493,共32页
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often... The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities. 展开更多
关键词 Smart cities digital twin AI-IOT framework predictive infrastructure management edge computing reinforcement learning optimization methods federated learning urban systems modeling smart governance
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Fast beam migration capable of dealing with intersecting events 认领 引用
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作者 Zhi-Miao Chang Fu-Xing Han +4 位作者 Zheng-Hui Gao Zhang-Qing Sun Shou-Dong Huo Gang Li Ming Zhang 《Petroleum Science》 SCIE EI CAS CSCD 2026年第1期190-204,共15页
Fast beam migration(FBM),characterized by its super-high efficiency in velocity model building,consists of three main steps:beam forming,beam propagation,and image forming.The super-high efficiency is achieved by beam... Fast beam migration(FBM),characterized by its super-high efficiency in velocity model building,consists of three main steps:beam forming,beam propagation,and image forming.The super-high efficiency is achieved by beam forming,as it needs only to be performed once for one dataset and is independent of velocity,and the other two steps take relatively little time.However,compared to the beam-propagation and image-forming steps,the beam-forming step is still quite time-consuming owing to the high-dimensional computing problem of estimating the source and receiver slope orientation of a beam.Furthermore,previous methods for estimating the source and receiver slope orientation of a beam struggled to deal with intersecting events,leading to poor imaging results for complex subsurface structures,such as unconformities or faults,where events often intersect.We propose the use of a three-step multimodal optimization method based on the neighborhood crowding differential evolution(NCDE)algorithm to estimate the source and receiver slope orientation of a beam during the beam-forming step,which can quickly and accurately obtain slope orientations when events intersect.We first test the three-step multimodal optimization algorithm on a 3D super-gather and provide the parameter criteria.We then apply the FBM based on the three-step multimodal optimization algorithm to the Marmousi 2 and 3D SEG/EAGE salt models.Both results demonstrate that the proposed method can image intersecting events well and that the imaging quality of complex zones is improved.We also apply the proposed method to a 2D offshore seismic dataset containing abundant intersecting events,which validates the practicality of the proposed method. 展开更多
关键词 Fast beam migration(FBM) Intersecting events Multimodal optimization method Neighborhood crowding differential evolution(NCDE)algorithm High-dimensional computing problem
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Optimization of Thermoplastic Elastomer (TPE) Components for Aerospace Structures Using Computerized Data-Driven Design 认领 引用
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作者 Adwaa Mohammed Abdulmajeed Duaa Abdul Rida Musa +2 位作者 Ola Abdul Hussain Emad Kadum Njim Royal Madan 《Computers, Materials & Continua》 SCIE EI 2026年第6期766-794,共29页
A data-driven optimization framework that integrates machine learning surrogate models,finite element analysis(FEA),and a multi-objective optimization algorithm is used in this study for developing thermoplastic elast... A data-driven optimization framework that integrates machine learning surrogate models,finite element analysis(FEA),and a multi-objective optimization algorithm is used in this study for developing thermoplastic elastomer(TPE)parts for aerospace applications.By using FEA simulations and experiments,a database of input design parameters(e.g.,geometry and structural shape modifier)is generated.Afterwards,we train surrogate models(e.g.,Gaussian Process Regression,neural networks)to approximate mappings from design space to performance space.Finally,we propose Pareto-optimal TPE designs using the surrogate embedded in a multi-objective optimization loop(such as NSGA-Ⅱ or gradient-based methods).The novelty of this approach is demonstrated by employing highly simplified surrogate models,including an artificial neural network(ANN)with 10 hidden neurons trained on analytically generated synthetic data.The proposed methodology has been validated using an aerospace-related case study:a vibration-damping plate.Compared with the baseline configuration,Pareto-optimal designs identified by the proposed framework achieved a reduction in maximum deflection of 23%-28%and a reduction in von Mises stress of 18%-24%,depending on the selected trade-off solution,as the number of full FEA simulations required for optimization was reduced from 500 to 50.This framework enables faster design of TPE components for aerospace systems.Validation against high-fidelity ANSYS simulations showed a mean error of~1.18%and a maximum deviation of~2.6%. 展开更多
关键词 TPE aerospace structures surrogate modelling data-driven optimization multi-objective optimization method FEM
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Extraction of Stratospheric Aerosol Extinction Profiles from Limb-Scattering Signals Measured by the BLS onboard the Tiangong-2 Space Laboratory 认领 引用
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作者 Song LIU Peng ZHANG +3 位作者 Lin CHEN Na Xu Minzheng DUAN Daren LYU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第6期1212-1225,共14页
Stratospheric aerosol extinction profiles are crucial for studying climate change and various atmospheric physical and chemical processes.Limb observations are among the most effective methods for obtaining global str... Stratospheric aerosol extinction profiles are crucial for studying climate change and various atmospheric physical and chemical processes.Limb observations are among the most effective methods for obtaining global stratospheric aerosol extinction profiles.In this paper,based on the color-ratio and optimal estimation methods,aerosol extinction profiles between 10 and 35 km were successfully extracted from limb-scattering signals measured by the Backward Limb Spectrometer(BLS)onboard the Tiangong-2 space laboratory.The aerosol extinction profiles derived from BLS were compared with those from the OMPS-LP v2.0 aerosol product,and the results showed good consistency.Using the average profile of each pair of BLS and OMPS-LP cross-observations as a reference,the mean relative errors of BLS are generally within±15%between 15 and 30 km,with a correlation coefficient of 0.955.However,larger errors may occur below 15 km.Sensitivity analysis indicates that the larger errors at lower altitudes are attributed to inaccuracies in the tangent height and the stratospheric aerosol particle size distribution model,both of which affect the accuracy of the final retrievals. 展开更多
关键词 stratospheric aerosols aerosol extinction profile limb scattering Tiangong-2 optimal estimation method
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Generative Adversarial Networks for Image Super-Resolution: A Survey 认领 引用
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作者 Ziang Wu Xuanyu Zhang +3 位作者 Yinbo Yu Qi Zhu Jerry Chun-Wei Lin Chunwei Tian 《Computers, Materials & Continua》 SCIE EI 2026年第6期72-117,共46页
Image super-resolution is a significant area in the field of image processing,with broad applications across multiple domains.In recent years,advancements in Generative Adversarial Networks(GANs)have led to an increas... Image super-resolution is a significant area in the field of image processing,with broad applications across multiple domains.In recent years,advancements in Generative Adversarial Networks(GANs)have led to an increased adoption of GAN-based methods in image super-resolution,yielding remarkable results.However,there is still a limited amount of research that systematically and comprehensively summarizes the various GAN-based techniques for image super-resolution.This paper provides a comparative study that elucidates the application differences of GANs in this field.We begin by reviewing the development of GANs and introducing their popular variants used in image applications.Subsequently,we systematically analyze the theoretical motivations,implementation approaches,and technical distinctions of GAN-based optimization methods and discriminative learning from three perspectives:supervised,semi-supervised,and unsupervised learning.We examine these methods concerning their integration of different network architectures,prior knowledge,loss functions,and multitask strategies.Furthermore,we conduct a systematic comparison of state-of-the-art GAN methods through quantitative and qualitative analyses using publicly available super-resolution datasets.In addition to traditional metrics such as PSNR and SSIM in our quantitative analysis,we also consider complexity and running time as reference standards to better align the evaluation with practical application demands.Finally,we identify several challenges currently faced by GANs in the domain of image super-resolution,including issues related to training stability and the need for improved evaluation metrics.We outline future research directions aimed at enhancing the robustness and efficiency of GAN-based super-resolution techniques,emphasizing the importance of integration with other machine learning frameworks to further advance this exciting field. 展开更多
关键词 SISR GANs optimization methods and discriminative learning
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Design method of optimal control schedule for the adaptive cycle engine steady-state performance 认领 引用 被引量：12
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作者 Yihao XU Hailong TANG Min CHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2022年第4期148-164,共17页
The alternative working modes and flexible working states are the outstanding features of an adaptive cycle engine, with a proper control schedule design being the only way to exploit the performance of such an engine... The alternative working modes and flexible working states are the outstanding features of an adaptive cycle engine, with a proper control schedule design being the only way to exploit the performance of such an engine. However, unreasonable design in the control schedule causes not only performance deterioration but also serious aerodynamic stability problems. Thus, in this work,a hybrid optimization method that automatically chooses the working modes and identifies the optimal and smooth control schedules is proposed, by combining the differential evolution algorithm and the Latin hypercube sampling method. The control schedule architecture does not only optimize the engine steady-state performance under different working modes but also solves the control-schedule discontinuity problem, especially during mode transition. The optimal control schedules are continuous and almost monotonic, and hence are strongly suitable for a control system, and are designed for two different working conditions, i.e., supersonic and subsonic throttling,which proves that the proposed hybrid method applies to various working conditions. The evaluation demonstrates that the proposed control method optimizes the engine performance, the surge margin of the compression components, and the range of the thrust during throttling. 展开更多
关键词 Adaptive cycle engine Control schedule design Hybrid optimization method Mode transition Performance optimization
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A D-optimal Multi-position Calibration Method for Dynamically Tuned Gyroscopes 认领 引用 被引量：5
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作者 FU Li ZHU Yongquan +1 位作者 WANG Lingling WANG Xinling 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2011年第2期210-218,共9页
This paper presents a novel experimental design to greatly improve the calibration accuracy of the acceleration-insensitive bias and the acceleration-sensitive bias of the dynamically tuned gyroscopes(DTGs).In order t... This paper presents a novel experimental design to greatly improve the calibration accuracy of the acceleration-insensitive bias and the acceleration-sensitive bias of the dynamically tuned gyroscopes(DTGs).In order to reduce experimental cost,the D-optimal criteria with constraints are constructed.The turntable positions and the number of test points are chosen to build D-optimal experimental designs.The D-optimal experimental designs are tested by multi-position calibration experiment for tactical-grade DTGs.Test results show that,with the same cost,the fit uncertainty is reduced by about 50%by using the D-optimal 8-position experimental procedure,compared to using a defacto standard experimental procedure in ANSI/IEEE Std 813-1988.Furthermore,the new experimental procedure almost achieves optimal accuracy with only 12-position which is half the cost of the widely adopted 24-position experimental procedure for achieving optimal accuracy. 展开更多
关键词 optimization methods calibration gyroscopes error compensation design for testability
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2D multi-scale hybrid optimization method for geophysical inversion and its application 认领 引用 被引量：4
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作者 潘纪顺 王新建 +4 位作者 张先康 徐朝繁 Zhao Ping 田晓峰 潘素珍 《Applied Geophysics》 SCIE 2009年第4期337-348,394,共12页
Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. ... Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust. 展开更多
关键词 multi-scale seismic travel-time tomography hybrid optimization method inversion A＇nyemaqen suture zone
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Gauss optimization method for the dynamics of unilateral contact of rigid multibody systems 认领 引用 被引量：9
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作者 Wenli Yao Liusong Yang Mingming Guo 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2021年第3期494-506,I0003,共13页
The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimiz... The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimization model for multibody system dynamics with multi-point contact and collision is established.The paper presents the study of the numerical solution scheme,in which particle swarm optimization method is used to deal with the corresponding optimization model.The article also presents the comparison of the Gauss optimization method(GOM)and the hybrid linear complementarity method(i.e.combining differential algebraic equations(DAEs)and linear complementarity problems(LCP)),commonly used to solve the dynamic contact problem of multibody systems with bilateral constraints.The results illustrate that,the GOM has the same advantage of dynamical modelling with LCP and when the redundant constraint exists,the GOM always has a unique solution and so no additional processing is needed,whereas the corresponding DAE-LCP method may have singular cases with multiple solutions or no solutions.Using numerical examples,the GOM is verified to effectively solve the dynamics of multibody systems with redundant unilateral and bilateral constraints without additional redundancy processing.The GOM can also be applied to the optimal control of systems in the future and combined with the parameter optimization of systems to handle dynamic problems.The work given provides the dynamics and control of the complex system with a new train of thought and method. 展开更多
关键词 Contact Collision Redundant constraint Gauss principle of least constraint Optimization method
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Design of small-scale gradient coils in magnetic resonance imaging by using the topology optimization method 认领 引用 被引量：3
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作者 Hui Pan Feng Jia +3 位作者 Zhen-Yu Liu Maxim Zaitsev Juergen Hennig Jan G Korvink 《Chinese Physics B》 SCIE EI CAS CSCD 2018年第5期91-100,共10页
A topology optimization method based on the solid isotropic material with penalization interpolation scheme is utilized for designing gradient coils for use in magnetic resonance microscopy.Unlike the popular stream f... A topology optimization method based on the solid isotropic material with penalization interpolation scheme is utilized for designing gradient coils for use in magnetic resonance microscopy.Unlike the popular stream function method,the proposed method has design variables that are the distribution of conductive material.A voltage-driven transverse gradient coil is proposed to be used as micro-scale magnetic resonance imaging(MRI)gradient coils,thus avoiding introducing a coil-winding pattern and simplifying the coil configuration.The proposed method avoids post-processing errors that occur when the continuous current density is approximated by discrete wires in the stream function approach.The feasibility and accuracy of the method are verified through designing the z-gradient and y-gradient coils on a cylindrical surface.Numerical design results show that the proposed method can provide a new coil layout in a compact design space. 展开更多
关键词 topology optimization method gradient coils solid isotropic material with penalization magnetic resonance imaging
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