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Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets 认领 引用 被引量：1
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作者 Peichen Zhao Qi Yue Zhibin Deng 《Intelligent Automation & Soft Computing》 SCIE 2023年第7期849-873,共25页
In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the... In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear. 展开更多
关键词 Two-sided matching decision-making(TSMDM) probabilistic hesitant fuzzy set(PHFS) the technique for order preference by similarity to ideal solution(TOPSIS) multi-attribute
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Exploring the evolution and collaboration in two-sided matching:a comprehensive bibliometric and topic modeling analysis 认领 引用
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作者 Xiaorong He Bo Xiang +1 位作者 Zeshui Xu Dejian Yu 《International Journal of Intelligent Computing and Cybernetics》 EI 2025年第1期1-32,共32页
Purpose-This study aims to provide a comprehensive analysis of two-sided matching(TSM)research,an interdisciplinary field that integrates both theoretical and practical perspectives.By examining 756 research articles ... Purpose-This study aims to provide a comprehensive analysis of two-sided matching(TSM)research,an interdisciplinary field that integrates both theoretical and practical perspectives.By examining 756 research articles from the Web of Science database,this paper seeks to identify key trends,collaboration patterns and emerging research topics within the TSM domain.Design/methodology/approach-The research utilizes bibliometric analysis combined with a structural topic model to analyze TSM-related articles published between January 1,2000,and September 30,2022.The study identifies leading subfields,journals,countriesegions and institutions based on publication volume,total citations and average citations per article.Interaction and collaboration patterns among these entities are examined through co-occurrence and coupling networks.Additionally,five major research topics are identified and explored using topic modeling and co-word networks.This hybrid knowledge mining approach better reveals the inherent structural changes in topic clusters.Topic distribution and network analysis are beneficial in capturing the attention allocation of different entities to knowledge.Findings-The analysis reveals five prominent research topics in TSM:communication resource allocation,stable matching research,computing task assignment,TSM decision-making and market matching mechanism design.These topics represent the main directions of TSM research.The study also uncovers a shift in research focus from theoretical aspects to practical applications.Furthermore,the distribution of knowledge and interaction patterns among key entities align with the identified research trends.Originality/value-This study offers a novel and detailed overview of TSM research highlighting significant trends and collaboration patterns within the field.By integrating bibliometric methods with structural topic modeling the study provides unique insights into the evolution of TSM research making it a valuable resource for both academic and professional communities. 展开更多
关键词 Two-sided matching Structural topic model Bibliometric analysis Literature review Topic migration
The Aviation Technology Two-Sided Matching with the Expected Time Based on the Probabilistic Linguistic Preference Relations 认领 引用 被引量：9
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作者 Bo Li Yi-Xin Zhang Ze-Shui Xu 《Journal of the Operations Research Society of China》 EI CSCD 2020年第1期45-77,共33页
The two-sided matching has been widely applied to the decision-making problems in the field of management.With the limited working experience,the two-sided agents usually cannot provide the preference order directly f... The two-sided matching has been widely applied to the decision-making problems in the field of management.With the limited working experience,the two-sided agents usually cannot provide the preference order directly for the opposite agent,but rather to provide the preference relations in the form of linguistic information.The preference relations based on probabilistic linguistic term sets(PLTSs)not only allowagents to provide the evaluation with multiple linguistic terms,but also present the different preference degrees for linguistic terms.Considering the diversities of the agents,they may provide their preference relations in the form of the probabilistic linguistic preference relation(PLPR)or the probabilistic linguistic multiplicative preference relation(PLMPR).For two-sided matching with the expected time,we first provide the concept of the time satisfaction degree(TSD).Then,we transform the preference relations in different forms into the unified preference relations(u-PRs).The consistency index to measure the consistency of u-PRs is introduced.Besides,the acceptable consistent u-PRs are constructed,and an algorithm is proposed to modify the unacceptable consistent u-PRs.Furthermore,we present the whole two-sided matching decisionmaking process with the acceptable consistent u-PRs.Finally,a case about aviation technology suppliers and demanders matching is presented to exhibit the rationality and practicality of the proposed method.Some analyses and discussions are provided to further demonstrate the feasibility and effectiveness of the proposed method. 展开更多
关键词 Two-sided matching Time satisfaction degree Probabilistic linguistic term sets Preference relation Aviation technology
Suitable area selection method based on scene matching level segmentation 认领 引用
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作者 Chao YANG Yuanxin YE +3 位作者 Renyuan LIU Chengjia FAN Liang ZHOU Jiwei DENG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第2期356-369,共14页
The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which ... The selection of a suitable navigation area is pivotal in aircraft scene matching guidance technology.This study addresses the challenge of identifying suitable reference image ranges for precise scene matching,which is crucial for enhancing aircraft positioning accuracy.Traditional methods for image matchability analysis are often limited by their reliance on manual feature parameter design and threshold-based filtering,resulting in suboptimal accuracy and efficiency.This paper proposes a novel network architecture for selecting suitable navigation areas using image Matching Level Segmentation(MLSNet).The approach involves two key innovations:a method for generating segmentation labels that quantify matchability levels and an end-to-end network architecture for rapid and precise prediction of reference image matchability segmentation maps.The network includes two core modules:the saliency analysis module uses multi-layer convolutional networks to accurately detect image saliency features across various levels and scales;the multidimensional attention module utilizes attention mechanisms to focus on feature channels and spatial neighborhood scenes to assess the image’s matchability.Our method was rigorously tested on an extensive collection of remote sensing images,where it was benchmarked against a range of both traditional and cutting-edge deep learning methods.The findings indicate that MLSNet is significantly superior to traditional methods in accuracy and efficiency of matchability analysis,and is also relatively ahead of state-of-the-art deep learning models. 展开更多
关键词 Deep learning Image matching level segmentation Optical Scene matching navigation Suitable matching area selection
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Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment 认领 引用
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作者 Qi Yue Zhibin Deng 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第5期1603-1623,共21页
In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE ... In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE preference matrix is transformed into the normalized HFE preference matrix.On this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated.Then,the normalized HFEs are transformed into agent satisfactions.Considering the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed.Based on the agent satisfaction matrix,the matching intention matrix of two-sided agents is built.According to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set up.Furthermore,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions.Using the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is obtained.Finally,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method. 展开更多
关键词 Two-sided matching stable matching hesitant fuzzy element matching intention programming model
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A facies-constrained flow-network model for fast history matching and production optimization of polymer flooding reservoirs 认领 引用
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作者 Guo-Yu Qin Xia Yan +4 位作者 Kai Zhang Li-Ming Zhang Qi Zhang Ming-Xin Zhang Chen-Yang Wang 《Petroleum Science》 SCIE EI CAS CSCD 2026年第6期3408-3438,共31页
With the rising water cut in mature oil fields,polymer flooding has emerged as a critical Enhanced Oil Recovery(EOR)technique.However,high-fidelity numerical simulations for history matching and polymer flooding optim... With the rising water cut in mature oil fields,polymer flooding has emerged as a critical Enhanced Oil Recovery(EOR)technique.However,high-fidelity numerical simulations for history matching and polymer flooding optimization remain computationally intensive,limiting their practicality for ClosedLoop Reservoir Management(CLRM),which is inherently dependent on rapid iterative simulations for real-time model updating and operational decision-making.Although physics-based data-driven flownetwork models,such as General-Purpose Simulator-powered Network model(GPSNet),can accelerate simulations,their lack of geological constraints compromises predictive reliability.To address this limitation,we propose a novel facies-constrained flow-network model(GPSNet-FC)within the GPSNet framework.This model simplifies reservoir geometry into a 1D discretized grid between wells while incorporating sedimentary facies boundaries identified through edge detection and level-set methods.Grid properties are assigned and calibrated based on facies-specific attributes to ensure geological consistency.GPSNet-FC is applied to history matching using the Ensemble Smoother with Multiple Data Assimilation(ESMDA)and to polymer flooding optimization via the Differential Evolution(DE)algorithm.Numerical case studies validate the method,demonstrating that GPSNet-FC outperforms the original GPSNet in both reliability and accuracy.By integrating facies-based geological constraints,this approach reduces non-uniqueness in history matching and enables rapid and accurate decision-making fo r polymer flooding strategies.This work advances the integration of geological data into physics-based data-driven models,offering a robust and efficient tool for the CLRM of polymer flooding reservoirs. 展开更多
关键词 Physics-based data-driven model Sedimentary facies constraints Polymer flooding History matching Production optimization
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Vortex matching effects and flux dynamics manipulation in MgB2 thin films via He-FIB-induced periodic artificial pinning centers 认领 引用
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作者 Ying Han Dali Yin +4 位作者 Xinwei Cai Yan Zhang Yue Wang Lifeng Tian Zizhao Gan 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第6期829-837,共9页
TFlux dynamics,which describes the behavior of magnetic vortices in type-Ⅱsuperconductors,governs macroscopic electromagnetic properties of superconducting materials.Recently,cutting-edge approaches utilizing artific... TFlux dynamics,which describes the behavior of magnetic vortices in type-Ⅱsuperconductors,governs macroscopic electromagnetic properties of superconducting materials.Recently,cutting-edge approaches utilizing artificial periodic nanostructures for active control of the pinning centers help to deepen the understanding of relevant mechanisms of flux dynamics.This study demonstrates the controlled introduction of large-scale,periodic artificial pinning centers(APCs)in MgB2 superconducting thin films to manipulate flux dynamics.Using focused helium ion beam(He-FIB)irradiation,we fabricated a square array of nanoscale columnar artificial pinning centers with a period of 100 nm on a 30 nm MgB2 superconducting thin film.Magnetoresistance measurements near the critical temperature(Tc)reveal a pronounced vortex matching effect,evidenced by sharp resistance minima(dips)at specific integer and fractional magnetic matching fields.This effect is shown to be highly dependent on external parameters such as temperature,driving current,and the angle of the magnetic field.Furthermore,the large-area irradiation systematically suppresses Tcand broadens the superconducting transition of the film.This work establishes He-FIB as a potent tool for advanced flux pinning engineering and provides a comprehensive understanding of flux dynamics in superconductors with periodic pinning landscapes. 展开更多
关键词 vortex matching effects periodic artificial pinning centers MgB2 focused helium ion beam
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Identication and Analysis of Aerodynamic Sound Sources in Wind Turbines Based on the Integration of Time-Domain De-Doppler and Orthogonal Matching Pursuit Techniques 认领 引用
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作者 Peng Wang Zhiying Gao +4 位作者 Yongyan Chen Rina Su Yefei Bai Jianlong Ma Tianhao Zhang 《Energy Engineering》 EI 2026年第6期292-315,共24页
We propose a novel procedure,Time-Domain De-Dopplerized Orthogonal Matching Pursuit deconvolution approach for the mapping of acoustic sources(TD-OMP-DAMAS),for separating aerodynamic noise sources distributed across ... We propose a novel procedure,Time-Domain De-Dopplerized Orthogonal Matching Pursuit deconvolution approach for the mapping of acoustic sources(TD-OMP-DAMAS),for separating aerodynamic noise sources distributed across wind turbine blades(WTB),a task that is typically hindered by mutual interference and spatial mixing.e proposed procedure is a two-stage,hybrid de-Doppler/sparse-reconstruction algorithm based on timedomain de-Doppler(TD,Stage 1)and an orthogonal matching pursuit(OMP)-based deconvolution scheme(Stage 2),enabling sparse-reconstruction techniques to be eectively applied in rotating-source scenarios.e method is validated using both simulated rotating-source data and wind-tunnel measurements,and its performance is systematically compared with several conventional approaches,including conventional beamforming(CBF),time-domain de-Doppler beamforming(TD-BF),and time-domain de-Doppler deconvolution approach for the mapping of acoustic sources(TD-DAMAS).Numerical results demonstrate that TD-OMP-DAMAS achieves the smallest localization error and the highest spatial resolution among all tested algorithms,while also maintaining strong robustness under low signal-to-noise ratio conditions and requiring signicantly fewer iterations than TD-DAMAS to accurately converge to the true source positions.Wind-tunnel tests further show that,under an inow velocity of 6 m/s and a tip-speed ratio of 4.5,the method improves spatial resolution by approximately 89%compared with CBF,conrming its superior capability in separating aerodynamic sources located on dierent WTB. 展开更多
关键词 Wind turbine noise source identication DAMAS orthogonal matching pursuit
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Waveform-matching reverse time migration for local earthquakes 认领 引用
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作者 Lanshu Bai Qingju Wu Ruiqing Zhang 《Earthquake Science》 CAS CSCD 2026年第2期125-139,共15页
With the increasing use of passive seismic data,developing seismic reflection imaging methods based on passive data is of considerable practical significance.This study presents a waveform-matching reverse time migrat... With the increasing use of passive seismic data,developing seismic reflection imaging methods based on passive data is of considerable practical significance.This study presents a waveform-matching reverse time migration for the primary reflected data from local earthquakes.In order to mitigate inconsistencies in frequency band and energy across earthquakes of different magnitudes,we first establish reference seismic waveform with standardized dominant frequency and magnitude.A matching operator is derived for each event by matching its waveforms with the reference waveform.This operator is then applied via convolution to all waveforms,producing standardized seismic waveforms with consistent wavelet features.The reshaped waveforms are then subjected to reverse time migration using an impedance imaging condition for primary reflections.To suppress strong energy interference near the hypocenters,both illumination compensation and three-dimensional Smoothed Spherical Mask centered on each source are used.Numerical tests using both simple two-layer model and fault-containing model demonstrate that the new method is robust and effective.The reverse time migration of primary reflected data of local earthquakes accurately images underground impedance boundaries such as stratum interfaces and fault planes,showing its promise for future application in seismically active fault zones. 展开更多
关键词 passive seismic data local earthquake waveform matching reverse time migration primary reflected data
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Edge-Intelligent Photovoltaic Fault Localization via NAS-Optimized Feature-Space Sub-Pixel Matching 认领 引用
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作者 Hongjiang Wang Jian Yu +3 位作者 Tian Zhang Na Ren Nan Zhang Zhenyu Liu 《Computers, Materials & Continua》 SCIE EI 2026年第6期1108-1135,共28页
The rapid deployment of Industrial Internet of Things(IIoT)systems,such as large-scale photovoltaic(PV)power stations in modern power grids,has created a strong demand for edge-intelligent fault localization methods t... The rapid deployment of Industrial Internet of Things(IIoT)systems,such as large-scale photovoltaic(PV)power stations in modern power grids,has created a strong demand for edge-intelligent fault localization methods that can operate reliably under strict computational and memory constraints.In this work,we propose an edge-intelligent photovoltaic fault localization framework that integrates intelligent computation with classical sub-pixel optimization.The framework adopts a modular,edge-oriented design in which a radial basis function(RBF)network is first employed as a lightweight screening module to enable conditional execution,thereby reducing unnecessary computation for non-faulty samples.For suspicious samples,a compact convolutional feature extractor is activated to generate discriminative representations.The architecture of this feature extractor is automatically optimized using neural architecture search(NAS)in an offline design stage,explicitly balancing localization accuracy and computational efficiency for industrial edge hardware.Sub-pixel displacement estimation and recursive partitioning are then performed in the learned feature space using a sum of squared differences-based,preserving the mathematical transparency of classical sub-pixel matching while significantly improving robustness to thermal noise and background interference.Unlike large end-to-end detection models,the proposed framework combines intelligent feature representation with interpretable localization mechanisms,resulting in a flexible and resource-efficient solution for edge deployment.Experimental results on a photovoltaic infrared fault image dataset demonstrate that the proposed NAS-optimized feature-space sub-pixel matching framework achieves more stable fault localization than other baselines,with only marginal additional computational overhead. 展开更多
关键词 Edge intelligence neural architecture search sub-pixel localization feature-based matching photovoltaic fault localization industrial internet of things
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TransFM:Visible-to-Infrared Image Translation via Flow Matching 认领 引用
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作者 Meiqi Gong Hao Zhang +1 位作者 Bingwei Hui Jiayi Ma 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第5期1239-1241,共3页
Dear Editor,Due to the scarcity of high-quality infrared data,translating visible images to infrared has become a practical solution to meet the growing demand for infrared images in low-light and adverse conditions.D... Dear Editor,Due to the scarcity of high-quality infrared data,translating visible images to infrared has become a practical solution to meet the growing demand for infrared images in low-light and adverse conditions.Due to the large modality gap and limited prior information,existing visible-to-infrared(VIS-to-IR)image translation methods often struggle with poor structural preservation,unclear cross-modal correspondence,and loss of thermal details. 展开更多
关键词 visible infrared visible images structural preservation flow matching modality gap cross modal correspondence infrared images thermal details
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Robust Noise Identifi cation and Data Reconstruction for Marine Magnetotelluric Time-Domain Data using STA/LTA and Compressive Sensing with Orthogonal Matching Pursuit 认领 引用
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作者 Yun-sheng Zhao Ming-zhen Zhang +3 位作者 Min-gui Cai Yan Gao Zhan-xiang He Jian-ping Li 《Applied Geophysics》 SCIE CSCD 2026年第2期720-734,870,871,共15页
Marine magnetotelluric(MMT)sounding is a vital geophysical technique used for imaging subsurface electrical conductivity structures beneath the seafl oor.However,MMT data recorded in oceanic environments are often sev... Marine magnetotelluric(MMT)sounding is a vital geophysical technique used for imaging subsurface electrical conductivity structures beneath the seafl oor.However,MMT data recorded in oceanic environments are often severely contaminated by various noise sources,including oceanic wave and current eff ects,ship movements,and instrumental noise.This noise can signifi cantly degrade data quality,impairing subsequent data processing and interpretation.Traditional global filtering methods often distort or remove valuable signal components along with the noise.Furthermore,simply excising noisy segments creates data gaps that compromise subsequent frequency-domain analysis.Therefore,a targeted,two-stage approach is necessary to first accurately identify localized,transient noise and then reconstruct only the corrupted segments,preserving the integrity of the clean signal.This paper presents a novel approach that eff ectively addresses both challenges.Firstly,a Short-Term Average/Long-Term Average algorithm is applied for the semiautomatic identifi cation and fl agging of noisy segments,successfully detecting both transient bursts and quasiperiodic disturbances.Secondly,to ensure data continuity and fi delity,a data reconstruction algorithm based on Compressive Sensing(CS)theory is employed to reconstruct the corrupted data within the identifi ed noisy sections.Specifi cally,we use Orthogonal Matching Pursuit(OMP)to solve the CS reconstruction problem,taking advantage of the inherent sparsity of the underlying MMT signal in a transformed domain.The proposed methodology aims to enhance the signal-to-noise ratio and recover essential signal features,thus improving the reliability of MMT soundings.Application to real-world datasets demonstrates the effi cacy of the combined approach in suppressing complex noise patterns and reconstructing good-quality MMT time-series data. 展开更多
关键词 Marine Magnetotelluric Noise Identifi cation Data Reconstruction Short-Term Average/Long-Term Average Orthogonal Matching Pursuit
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Stable matching mechanism for multi-modal integration on mobility-as-a-service platform 认领 引用
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作者 WU Yating LAI Minghui 《Journal of Southeast University(English Edition)》 EI CAS 2026年第2期250-256,共7页
In mobility-as-a-service(MaaS)platforms integrating ridesharing with public transit,each rider-driver pair may have multiple potential matches via different transfer nodes,with users being self-interested with heterog... In mobility-as-a-service(MaaS)platforms integrating ridesharing with public transit,each rider-driver pair may have multiple potential matches via different transfer nodes,with users being self-interested with heterogeneous preferences.After generating all feasible integrated matches,a two-sided one-to-one stable matching model is formulated to maximize platform revenue,where each feasible match corresponds to a stability constraint embedding preference information.To solve this model efficiently,an iterative constraint-generation algorithm is designed.It repeatedly solves a restricted master problem to obtain a temporary solution and a subproblem to identify violated stability constraints,iterating until no violations remain.The proposed algorithm can significantly improve computational efficiency.Compared with a centralized matching benchmark with the blocking rate up to 75%,stable matching increases transit usage and user acceptance at the cost of a 31.43% reduction in average platform revenue.Riders experience longer detours with greater cost savings,whereas drivers exhibit the opposite pattern. 展开更多
关键词 mobility as a service stable matching constraint generation ridesharing public transit
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An image inpainting method based on multiple receptive fields and dynamic matching of damaged patterns 认领 引用
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作者 MENG Jiahao LIU Weirong +2 位作者 SHI Changhong LI Zhijun LIU Jie 《Journal of Southeast University(English Edition)》 EI CAS 2026年第1期121-130,共10页
Current image inpainting models are primarily designed to achieve a large receptive field(RF)using refinement networks to incorporate different scales.However,these models fail to adapt the use of different RFs to the... Current image inpainting models are primarily designed to achieve a large receptive field(RF)using refinement networks to incorporate different scales.However,these models fail to adapt the use of different RFs to the specific patterns of image damage,resulting in artifacts and semantic information confusion in repaired images.To address the problems of artifacts and semantic information confusion,inspired by different sensitivities of different RFs to inpainting the same image damaged patterns,this study proposes an image inpainting method based on multiple receptive fields(MRFs)and dynamic matching of damaged patterns.First,the parallel filter banks are used to extract the MRF feature groups.Second,the features are dynamically weighted and screened,guided by the mask image,to construct a relationship that adaptively matches the most relevant RF to each specific damaged pattern.A fast Fourier convolution based decoder is used to enhance the fusion of global contextual features during the reconstruction of high dimensional features into low dimensional images.Comparative experimental results show that the proposed method achieves better subjective and objective inpainting results on three public datasets:Paris StreetView,CelebA-HQ,and Places2. 展开更多
关键词 image inpainting generative adversarial networks multiple receptive fields(MRFs) dynamic matching of damaged patterns decoder with fast Fourier convolutional
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Research on grain supply and demand matching in the Beijing-Tianjin-Hebei region based on ecosystem service flows 认领 引用 被引量：1
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作者 Jiaxin Miao Peipei Pan +7 位作者 Bingyu Liu XiaowenYuan Zijun Pan Linsi Li Xinyun Wang Yuan Wang Yongqiang Cao Tianyuan Zhang 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2026年第2期460-480,共21页
A comprehensive assessment of grain supply,demand,and ecosystem service flows is essential for identifying grain movement pathways,ensuring regional grain security,and guiding sustainable management strategies.However... A comprehensive assessment of grain supply,demand,and ecosystem service flows is essential for identifying grain movement pathways,ensuring regional grain security,and guiding sustainable management strategies.However,current studies primarily focus on short-term grain provision services while neglecting the spatiotemporal variations in grain flows across different scales.This gap limits the identification of dynamic matching relationships and the formulation of optimization strategies for balancing grain flows.This study examined the spatiotemporal evolution of grain supply and demand in the Beijing-Tianjin-Hebei(BTH)region from 1980 to 2020.Using the Enhanced TwoStep Floating Catchment Area method,the grain provision ecosystem service flows were quantified,the changes in supply–demand matching under different grain flow scenarios were analyzed and the optimal distance threshold for grain flows was investigated.The results revealed that grain production follows a spatial distribution pattern characterized by high levels in the southeast and low levels in the northwest.A significant mismatch exists between supply and demand,and it shows a scale effect.Deficit areas are mainly concentrated in the northwest,while surplus areas are mainly located in the central and southern regions.As the spatial scale increases,the ecosystem service supply–demand ratio(SDR)classification becomes more clustered,while it exhibits greater spatial SDR heterogeneity at smaller scales.This study examined two distinct scenarios of grain provision ecosystem service flow dynamics based on 100 and 200 km distance thresholds.The flow increased significantly,from 2.17 to 11.81million tons in the first scenario and from 2.41 to 12.37 million tons in the second scenario over nearly 40 years,forming a spatial movement pattern from the central and southern regions to the surrounding areas.Large flows were mainly concentrated in the interior of urban centers,with significant outflows between cities such as Baoding,Shijiazhuang,Xingtai,and Hengshui.At the county scale,supply–demand matching patterns remained consistent between the grain flows in the two scenarios.Notably,incorporating grain flow dynamics significantly reduced the number of grain-deficit areas compared to scenarios without grain flow.In 2020,grain-deficit counties decreased by28.79 and 37.88%,and cities by 12.50 and 25.0%under the two scenarios,respectively.Furthermore,the distance threshold for achieving optimal supply and demand matching at the county scale was longer than at the city scale in both grain flow scenarios.This study provides valuable insights into the dynamic relationships and heterogeneous patterns of grain matching,and expands the research perspective on grain and ecosystem service flows across various spatiotemporal scales. 展开更多
关键词 Beijing-Tianjin-Hebei region grain provision ecosystem service grain flow supply and demand match distance threshold
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Leveraging Cyclic Redundancy Check for Improving Distribution Matching in Probabilistic Amplitude Shaping 认领 引用
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作者 Danish Ilyas Liu Rongke +2 位作者 Abdul Wakeel Alina Mirza Abdul Ghafoor 《China Communications》 SCIE EI CSCD 2026年第3期169-181,共13页
In this paper,we propose a novel cyclic redundancy check(CRC)-aided method to improve the energy efficiency of distribution matching(DM)algorithms based on fixed empirical distribution codebooks.The core design concep... In this paper,we propose a novel cyclic redundancy check(CRC)-aided method to improve the energy efficiency of distribution matching(DM)algorithms based on fixed empirical distribution codebooks.The core design concept is to map a subset of a DM codebook to the entire codebook.The mapping is identified by a binary vector that is convolved during the CRC encoding;thereby avoiding any additional overhead in a CRC-aided system.At the receiver(RX),the CRC check not only performs error detection but also identifies the mapping of the transmitted symbol sequences to the original input of the DM.With the information delivered by a quarter-sized codebook,fewer occurrence of high-energy symbols effectively reduces the average symbol energy and the rate-loss.The proposed method can be seamlessly integrated into any DM algorithm that uses fixed empirical distribution codebooks.We demonstrate its implementation in a polar-coded probabilistic amplitude shaping(PAS)system with CRC-aided successive cancellation list decoding.Using this architecture,we show an energy efficiency improvement of up to 26%and a signal-to-noise ratio improvement of up to 0.8 dB at a fixed target frame error rate of 10−3. 展开更多
关键词 cyclic redundancy check distribution matching probabilistic amplitude shaping
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Semantic-Guided Stereo Matching Network Based on Parallax Attention Mechanism and Seg Former 认领 引用
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作者 Zeyuan Chen Yafei Xie +2 位作者 Jinkun Li Song Wang Yingqiang Ding 《Computers, Materials & Continua》 SCIE EI 2026年第4期1322-1340,共19页
Stereo matching is a pivotal task in computer vision,enabling precise depth estimation from stereo image pairs,yet it encounters challenges in regions with reflections,repetitive textures,or fine structures.In this pa... Stereo matching is a pivotal task in computer vision,enabling precise depth estimation from stereo image pairs,yet it encounters challenges in regions with reflections,repetitive textures,or fine structures.In this paper,we propose a Semantic-Guided Parallax Attention Stereo Matching Network(SGPASMnet)that can be trained in unsupervised manner,building upon the Parallax Attention Stereo Matching Network(PASMnet).Our approach leverages unsupervised learning to address the scarcity of ground truth disparity in stereo matching datasets,facilitating robust training across diverse scene-specific datasets and enhancing generalization.SGPASMnet incorporates two novel components:a Cross-Scale Feature Interaction(CSFI)block and semantic feature augmentation using a pre-trained semantic segmentation model,SegFormer,seamlessly embedded into the parallax attention mechanism.The CSFI block enables effective fusion ofmulti-scale features,integrating coarse and fine details to enhance disparity estimation accuracy.Semantic features,extracted by SegFormer,enrich the parallax attention mechanism by providing high-level scene context,significantly improving performance in ambiguous regions.Our model unifies these enhancements within a cohesive architecture,comprising semantic feature extraction,an hourglass network,a semantic-guided cascaded parallax attentionmodule,outputmodule,and a disparity refinement network.Evaluations on the KITTI2015 dataset demonstrate that our unsupervised method achieves a lower error rate compared to the original PASMnet,highlighting the effectiveness of our enhancements in handling complex scenes.By harnessing unsupervised learning without ground truth disparity needed,SGPASMnet offers a scalable and robust solution for accurate stereo matching,with superior generalization across varied real-world applications. 展开更多
关键词 Stereo matching parallax attention unsupervised learning convolutional neural network stereo correspondence
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Searchable Attribute-Based Encryption with Multi-Keyword Fuzzy Matching for Cloud-Based IoT 认领 引用
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作者 He Duan Shi Zhang Dayu Li 《Computers, Materials & Continua》 SCIE EI 2026年第2期872-896,共25页
Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudass... Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudassisted architecture faces two critical challenges:the untrusted cloud services and the separation of data ownership from control.Although Attribute-based Searchable Encryption(ABSE)provides fine-grained access control and keyword search over encrypted data,existing schemes lack of error tolerance in exact multi-keyword matching.In this paper,we proposed an attribute-based multi-keyword fuzzy searchable encryption with forward ciphertext search(FCS-ABMSE)scheme that avoids computationally expensive bilinear pairing operations on the IoT device side.The scheme supportsmulti-keyword fuzzy search without requiring explicit keyword fields,thereby significantly enhancing error tolerance in search operations.It further incorporates forward-secure ciphertext search to mitigate trapdoor abuse,as well as offline encryption and verifiable outsourced decryption to minimize user-side computational costs.Formal security analysis proved that the FCS-ABMSE scheme meets both indistinguishability of ciphertext under the chosen keyword attacks(IND-CKA)and the indistinguishability of ciphertext under the chosen plaintext attacks(IND-CPA).In addition,we constructed an enhanced variant based on type-3 pairings.Results demonstrated that the proposed scheme outperforms existing ABSE approaches in terms of functionalities,computational cost,and communication cost. 展开更多
关键词 Cloud computing Internet of Things ABSE multi-keyword fuzzy matching outsourcing decryption
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A Real-Time Task Scheduling Algorithm Based on Bilateral Matching Games in a Distributed Computing Environment 认领 引用
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作者 LI Shuo FANG Zuying +1 位作者 ZHOU Guoqiang DAI Guilan 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2026年第1期69-78,共10页
In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task exec... In the era of the Internet of Things,distributed computing alleviates the problem of insufficient terminal computing power by integrating idle resources of heterogeneous devices.However,the imbalance between task execution delay and node energy consumption,and the scheduling and adaptation challenges brought about by device heterogeneity,urgently need to be addressed.To tackle this problem,this paper constructs a multi-objective real-time task scheduling model that considers task real-time performance,execution delay,system energy consumption,and node interests.The model aims to minimize the delay upper bound and total energy consumption while maximizing system satisfaction.A real-time task scheduling algorithm based on bilateral matching game is proposed.By designing a bidirectional preference mechanism between tasks and computing nodes,combined with a multi-round stable matching strategy,accurate matching between tasks and nodes is achieved.Simulation results show that compared with the baseline scheme,the proposed algorithm significantly reduces the total execution cost,effectively balances the task execution delay and the energy consumption of compute nodes,and takes into account the interests of each network compute node. 展开更多
关键词 dispersed computing real-time task task scheduling bilateral matching game
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Real-Time Multi-Modal Image Matching Based on Lightweight Learning Model 认领 引用
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作者 Jixuan Li Chenzhong Gao +2 位作者 Desheng Weng Yute Li Wei Li 《Journal of Beijing Institute of Technology》 EI CAS 2026年第3期253-262,共10页
This paper proposes an efficient algorithm for real-time multi-modal image matching based on a lightweight feature fusion network,targeting the challenges of multi-modal image matching in multi-source data analysis.Th... This paper proposes an efficient algorithm for real-time multi-modal image matching based on a lightweight feature fusion network,targeting the challenges of multi-modal image matching in multi-source data analysis.The algorithm addresses significant multi-modal feature differences and real-time processing limitations by incorporating key technologies including reparameterization in convolutional neural networks,multi-scale image pyramids,and feature fusion modules.The matching process employs a coarse-to-fine strategy,ensuring robust performance in complex environments.Experimental results using multi-modal datasets demonstrate that the proposed algorithm achieves superior accuracy and speed,with a success rate of 98.3%and an average matching time of 30.51 ms per 500×500 image pair.These results highlight the practical value and strong generalization capability of the algorithm in real-time applications. 展开更多
关键词 image matching multi-modal images deep learning neural network lightweight
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