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Multi-Scale Vision Transformer with Dynamic Multi-Loss Function for Medical Image Retrieval and Classification 认领 引用
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作者 Omar Alqahtani Mohamed Ghouse +2 位作者 Asfia Sabahath Omer Bin Hussain Arshiya Begum 《Computers, Materials & Continua》 SCIE EI 2025年第5期2221-2244,共24页
This paper introduces a novel method for medical image retrieval and classification by integrating a multi-scale encoding mechanism with Vision Transformer(ViT)architectures and a dynamic multi-loss function.The multi... This paper introduces a novel method for medical image retrieval and classification by integrating a multi-scale encoding mechanism with Vision Transformer(ViT)architectures and a dynamic multi-loss function.The multi-scale encoding significantly enhances the model’s ability to capture both fine-grained and global features,while the dynamic loss function adapts during training to optimize classification accuracy and retrieval performance.Our approach was evaluated on the ISIC-2018 and ChestX-ray14 datasets,yielding notable improvements.Specifically,on the ISIC-2018 dataset,our method achieves an F1-Score improvement of+4.84% compared to the standard ViT,with a precision increase of+5.46% for melanoma(MEL).On the ChestX-ray14 dataset,the method delivers an F1-Score improvement of 5.3%over the conventional ViT,with precision gains of+5.0% for pneumonia(PNEU)and+5.4%for fibrosis(FIB).Experimental results demonstrate that our approach outperforms traditional CNN-based models and existing ViT variants,particularly in retrieving relevant medical cases and enhancing diagnostic accuracy.These findings highlight the potential of the proposedmethod for large-scalemedical image analysis,offering improved tools for clinical decision-making through superior classification and case comparison. 展开更多
关键词 Medical image retrieval vision transformer multi-scale encoding multi-loss function ISIC-2018 ChestX-ray14
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Multi-scale analysis of spatiotemporal evolution and driving factors of eco-environmental quality in a Ningxia irrigation district,China 认领 引用
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作者 LI Zequan CHAI Mingtang +4 位作者 ZHU Lei HE Junjie DING Yimin XU Fengkun XU Xiyuan 《Journal of Geographical Sciences》 SCIE CSCD 2026年第2期471-493,共23页
The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a mo... The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a modified remote sensing ecological index(MRSEI)was developed by incorporating evapotranspiration.Spatial and temporal patterns were analyzed using the coefficient of variation,spatial autocorrelation,and semi-variogram methods,while influencing factors were explored via the optimal parameter geographical detector model.The MRSEI’s first principal component loadings and rankings aligned with those of RSEI(average contribution:81.31%),effectively reflecting spatiotemporal variations.At sub-irrigation district and landscape scales,ecological quality was slightly lower than at the district level but remained stable.Moderate and good ecological grades accounted for 36.28%and 33.38%of the area,respectively,at the district scale,and the moderate grade reached 70.48%on smaller scales.Spatial heterogeneity intensified with decreasing scale,and human activity lost explanatory power below a 5 km range.Human factors mainly drove ecological differentiation at the district scale,while natural factors dominated at finer scales.The MRSEI offers a novel tool for ecological assessment in arid/semi-arid areas and supports scale-adapted ecological protection strategies. 展开更多
关键词 ecological environment quality multi-scales remote sensing ecological index spatial heterogeneity semi-variance function
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MSD-YOLO: A Multi-Scale and Detail-Enhancement Network for Traffic Sign Detection 认领 引用
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作者 Mingfang Li Damin Zhang +3 位作者 Qing He Chenglong Zhou Mingrong Li Xiaobo Zhou 《Computers, Materials & Continua》 SCIE EI 2026年第6期2248-2271,共24页
Traffic sign detection is a critical task in autonomous driving environmental perception.However,models often suffer from degraded detection performance in complex real-world scenarios due to variable target scales,bl... Traffic sign detection is a critical task in autonomous driving environmental perception.However,models often suffer from degraded detection performance in complex real-world scenarios due to variable target scales,blurred fine-grained features,and complex background interference.This paper proposes an improved YOLOv8n detection model,MSD-YOLO,to address these challenges.First,a Multi-scale Detail Enhancement Module(MDEM)is designed,which achieves targeted enhancement of edge features through high-frequency residual modulation and multi-scale cooperative attention.Second,an enhanced feature pyramid network termed SG-FPN is constructed.It introduces soft nearest neighbor interpolation(SNI)for semantic-spatial aligned feature fusion and employs enhanced lightweight convolution(GSConvE)to improve feature representation.Additionally,the Wise-ShapeIoU optimization loss function is adopted,integrating shape-aware geometric constraints and a dynamic sample weighting strategy to enhance the localization accuracy for traffic signs of different scales and shapes.Experiments on the TT100K dataset show that our method effectively improves detection performance,with mAP@0.5 and mAP@0.5:0.95 increasing by 3.1%and 2.7%,respectively,compared to the baseline YOLOv8n.Moreover,cross-dataset evaluations on CCTSDB and GTSDB show that the model exhibits good generalization capability and robustness.The experimental results indicate that the proposed method can enhance detection accuracy while maintaining efficient real-time inference,offering an effective solution for traffic sign detection in complex scenarios. 展开更多
关键词 Traffic sign detection YOLOv8n multi-scale feature fusion loss function
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Variable reward function-driven strategies for impulsive orbital attack-defense games under multiple constraints and victory conditions 认领 引用 被引量：3
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作者 Liran Zhao Sihan Xu +1 位作者 Qinbo Sun Zhaohui Dang 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2025年第9期159-183,共25页
This paper investigates impulsive orbital attack-defense(AD)games under multiple constraints and victory conditions,involving three spacecraft:attacker,target,and defender.In the AD scenario,the attacker aims to breac... This paper investigates impulsive orbital attack-defense(AD)games under multiple constraints and victory conditions,involving three spacecraft:attacker,target,and defender.In the AD scenario,the attacker aims to breach the defender's interception to rendezvous with the target,while the defender seeks to protect the target by blocking or actively pursuing the attacker.Four different maneuvering constraints and five potential game outcomes are incorporated to more accurately model AD game problems and increase complexity,thereby reducing the effectiveness of traditional methods such as differential games and game-tree searches.To address these challenges,this study proposes a multiagent deep reinforcement learning solution with variable reward functions.Two attack strategies,Direct attack(DA)and Bypass attack(BA),are developed for the attacker,each focusing on different mission priorities.Similarly,two defense strategies,Direct interdiction(DI)and Collinear interdiction(CI),are designed for the defender,each optimizing specific defensive actions through tailored reward functions.Each reward function incorporates both process rewards(e.g.,distance and angle)and outcome rewards,derived from physical principles and validated via geometric analysis.Extensive simulations of four strategy confrontations demonstrate average defensive success rates of 75%for DI vs.DA,40%for DI vs.BA,80%for CI vs.DA,and 70%for CI vs.BA.Results indicate that CI outperforms DI for defenders,while BA outperforms DA for attackers.Moreover,defenders achieve their objectives more effectively under identical maneuvering capabilities.Trajectory evolution analyses further illustrate the effectiveness of the proposed variable reward function-driven strategies.These strategies and analyses offer valuable guidance for practical orbital defense scenarios and lay a foundation for future multi-agent game research. 展开更多
关键词 Orbital attack-defense game Impulsive maneuver Multi-agent deep reinforcement learning Reward function design
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Multi-scale analysis of the spatial structure of China’s major function zoning 认领 引用 被引量：15
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作者 WANG Yafei FAN Jie 《Journal of Geographical Sciences》 SCIE CSCD 2020年第2期197-211,共15页
The spatial structures of China’s Major Function Zoning are important constraining indicators in all types of spatial planning and key parameters for accurately downscaling major functions.Taking the proportion of ur... The spatial structures of China’s Major Function Zoning are important constraining indicators in all types of spatial planning and key parameters for accurately downscaling major functions.Taking the proportion of urbanization zones,agricultural development zones and ecological security zones as the basic parameter,this paper explores the spatial structures of major function zoning at different scales using spatial statistics,spatial modeling and landscape metrics methods.The results show:First,major function zones have spatial gradient structures,which are prominently represented by latitudinal and longitudinal gradients,a coastal distance gradient,and an eastern-central-western gradient.Second,the pole-axis system structure and core-periphery structure exist at provincial scales.The general principle of the pole-axis structure is that as one moves along the distance axis,the proportion of urbanization zones decreases and the proportion of ecological security zones increases.This also means that the proportion of different function zones has a ring-shaped spatial differentiation principle with distance from the core.Third,there is a spatial mosaic structure at the city and county scale.This spatial mosaic structure has features of both spatial heterogeneity,such as agglomeration and dispersion,as well as of mutual,adjacent topological correlation and spatial proximity.The results of this study contribute to scientific knowledge on major function zones and the principles of spatial organization,and it acts as an important reference for China’s integrated geographical zoning. 展开更多
关键词 China major function zoning multi-scale spatial gradient pole-axis core-periphery spatial mosaic
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CT-MFENet:Context Transformer and Multi-Scale Feature Extraction Network via Global-Local Features Fusion for Retinal Vessels Segmentation 认领 引用
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作者 SHAO Dangguo YANG Yuanbiao +1 位作者 MA Lei YI Sanli 《Journal of Shanghai Jiaotong university(Science)》 EI 2025年第4期668-682,共15页
Segmentation of the retinal vessels in the fundus is crucial for diagnosing ocular diseases.Retinal vessel images often suffer from category imbalance and large scale variations.This ultimately results in incomplete v... Segmentation of the retinal vessels in the fundus is crucial for diagnosing ocular diseases.Retinal vessel images often suffer from category imbalance and large scale variations.This ultimately results in incomplete vessel segmentation and poor continuity.In this study,we propose CT-MFENet to address the aforementioned issues.First,the use of context transformer(CT)allows for the integration of contextual feature information,which helps establish the connection between pixels and solve the problem of incomplete vessel continuity.Second,multi-scale dense residual networks are used instead of traditional CNN to address the issue of inadequate local feature extraction when the model encounters vessels at multiple scales.In the decoding stage,we introduce a local-global fusion module.It enhances the localization of vascular information and reduces the semantic gap between high-and low-level features.To address the class imbalance in retinal images,we propose a hybrid loss function that enhances the segmentation ability of the model for topological structures.We conducted experiments on the publicly available DRIVE,CHASEDB1,STARE,and IOSTAR datasets.The experimental results show that our CT-MFENet performs better than most existing methods,including the baseline U-Net. 展开更多
关键词 retinal vessel segmentation context transformer(CT) multi-scale dense residual hybrid loss function global-local fusion
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Development and application of a multi-physics and multi-scale coupling program for lead-cooled fast reactor 认领 引用 被引量：11
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作者 Xiao Luo Chi Wang +4 位作者 Ze-Ren Zou Lian-Kai Cao Shuai Wang Zhao Chen Hong-Li Chen 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2022年第2期40-52,共13页
In this study,a multi-physics and multi-scale coupling program,Fluent/KMC-sub/NDK,was developed based on the user-defined functions(UDF)of Fluent,in which the KMC-sub-code is a sub-channel thermal-hydraulic code and t... In this study,a multi-physics and multi-scale coupling program,Fluent/KMC-sub/NDK,was developed based on the user-defined functions(UDF)of Fluent,in which the KMC-sub-code is a sub-channel thermal-hydraulic code and the NDK code is a neutron diffusion code.The coupling program framework adopts the"master-slave"mode,in which Fluent is the master program while NDK and KMC-sub are coupled internally and compiled into the dynamic link library(DLL)as slave codes.The domain decomposition method was adopted,in which the reactor core was simulated by NDK and KMC-sub,while the rest of the primary loop was simulated using Fluent.A simulation of the reactor shutdown process of M2LFR-1000 was carried out using the coupling program,and the code-to-code verification was performed with ATHLET,demonstrating a good agreement,with absolute deviation was smaller than 0.2%.The results show an obvious thermal stratification phenomenon during the shutdown process,which occurs 10 s after shutdown,and the change in thermal stratification phenomena is also captured by the coupling program.At the same time,the change in the neutron flux density distribution of the reactor was also obtained. 展开更多
关键词 Multi-physics and multi-scale coupling method User-defined functions Dynamic link library Thermal stratification Lead-cooled fast reactor
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Multi-scale spatial relationships between soil total nitrogen and influencing factors in a basin landscape based on multivariate empirical mode decomposition 认领 引用 被引量：1
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作者 ZHU Hongfen CAO Yi +3 位作者 JING Yaodong LIU Geng BI Rutian YANG Wude 《Journal of Arid Land》 SCIE CSCD 2019年第3期385-399,共15页
The relationships between soil total nitrogen(STN)and influencing factors are scale-dependent.The objective of this study was to identify the multi-scale spatial relationships of STN with selected environmental factor... The relationships between soil total nitrogen(STN)and influencing factors are scale-dependent.The objective of this study was to identify the multi-scale spatial relationships of STN with selected environmental factors(elevation,slope and topographic wetness index),intrinsic soil factors(soil bulk density,sand content,silt content,and clay content)and combined environmental factors(including the first two principal components(PC1 and PC2)of the Vis-NIR soil spectra)along three sampling transects located at the upstream,midstream and downstream of Taiyuan Basin on the Chinese Loess Plateau.We separated the multivariate data series of STN and influencing factors at each transect into six intrinsic mode functions(IMFs)and one residue by multivariate empirical mode decomposition(MEMD).Meanwhile,we obtained the predicted equations of STN based on MEMD by stepwise multiple linear regression(SMLR).The results indicated that the dominant scales of explained variance in STN were at scale 995 m for transect 1,at scales 956 and 8852 m for transect 2,and at scales 972,5716 and 12,317 m for transect 3.Multi-scale correlation coefficients between STN and influencing factors were less significant in transect 3 than in transects 1 and 2.The goodness of fit root mean square error(RMSE),normalized root mean square error(NRMSE),and coefficient of determination(R2)indicated that the prediction of STN at the sampling scale by summing all of the predicted IMFs and residue was more accurate than that by SMLR directly.Therefore,the multi-scale method of MEMD has a good potential in characterizing the multi-scale spatial relationships between STN and influencing factors at the basin landscape scale. 展开更多
关键词 intrinsic mode function multivariate empirical mode decomposition multi-scale spatial relationship sampling transect soil total nitrogen Chinese Loess Plateau
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A Quadrilateral Element-based Method for Calculation of Multi-scale Temperature Field 认领 引用 被引量：1
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作者 孙志刚 周超羡 +1 位作者 高希光 宋迎东 《Chinese Journal of Aeronautics》 SCIE EI CAS 2010年第5期529-536,共8页
In the analysis of functionally graded materials （FGMs）, the uncoupled approach is used broadly, which is based on homogenized material property and ignores the effect Of local micro-structural interaction. The high... In the analysis of functionally graded materials （FGMs）, the uncoupled approach is used broadly, which is based on homogenized material property and ignores the effect Of local micro-structural interaction. The higher-order theory for FGMs （HOTFGM） is a coupled approach that explicitly takes the effect of micro-structural gradation and the local interaction of the spatially variable inclusion phase into account. Based on the HOTFGM, this article presents a quadrilateral element-based method for the calculation of multi-scale temperature field （QTF）. In this method, the discrete cells are quadrilateral including rectangular while the surface-averaged quantities are the primary variables which replace the coefficients employed in the temperature function. In contrast with the HOTFGM, this method improves the efficiency, eliminates the restriction of being rectangular cells and expands the solution scale. The presented results illustrate the efficiency of the QTF and its advantages in analyzing FGMs. 展开更多
关键词 functionally graded materials higher-order theory temperature field multi-scale computing quadrilateral cell
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Two Stages Segmentation Algorithm of Breast Tumor in DCE-MRI Based on Multi-Scale Feature and Boundary Attention Mechanism 认领 引用
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作者 Bing Li Liangyu Wang +3 位作者 Xia Liu Hongbin Fan Bo Wang Shoudi Tong 《Computers, Materials & Continua》 SCIE EI 2024年第7期1543-1561,共19页
Nuclearmagnetic resonance imaging of breasts often presents complex backgrounds.Breast tumors exhibit varying sizes,uneven intensity,and indistinct boundaries.These characteristics can lead to challenges such as low a... Nuclearmagnetic resonance imaging of breasts often presents complex backgrounds.Breast tumors exhibit varying sizes,uneven intensity,and indistinct boundaries.These characteristics can lead to challenges such as low accuracy and incorrect segmentation during tumor segmentation.Thus,we propose a two-stage breast tumor segmentation method leveraging multi-scale features and boundary attention mechanisms.Initially,the breast region of interest is extracted to isolate the breast area from surrounding tissues and organs.Subsequently,we devise a fusion network incorporatingmulti-scale features and boundary attentionmechanisms for breast tumor segmentation.We incorporate multi-scale parallel dilated convolution modules into the network,enhancing its capability to segment tumors of various sizes through multi-scale convolution and novel fusion techniques.Additionally,attention and boundary detection modules are included to augment the network’s capacity to locate tumors by capturing nonlocal dependencies in both spatial and channel domains.Furthermore,a hybrid loss function with boundary weight is employed to address sample class imbalance issues and enhance the network’s boundary maintenance capability through additional loss.Themethod was evaluated using breast data from 207 patients at RuijinHospital,resulting in a 6.64%increase in Dice similarity coefficient compared to the benchmarkU-Net.Experimental results demonstrate the superiority of the method over other segmentation techniques,with fewer model parameters. 展开更多
关键词 Dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI) breast tumor segmentation multi-scale dilated convolution boundary attention the hybrid loss function with boundary weight
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Signal Separation and Instantaneous Frequency Estimation Based on Multi-scale Chirplet Sparse Signal Decomposition 认领 引用
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作者 于德介 罗洁思 史美丽 《Journal of Measurement Science and Instrumentation》 CAS 2010年第1期17-21,共5页
An approach based on multi-scale ehirplet sparse signal decomposition is proposed to separate the malti-component polynomial phase signals, and estimate their instantaneous frequencies. In this paper, we have generate... An approach based on multi-scale ehirplet sparse signal decomposition is proposed to separate the malti-component polynomial phase signals, and estimate their instantaneous frequencies. In this paper, we have generated a family of multi-scale chirplet functions which provide good local correlations of chirps over shorter time interval. At every decomposition stage, we build the so-called family of chirplets and our idea is to use a structured algorithm which exploits information in the family to chain chirplets together adaptively as to form the polyncmial phase signal component whose correlation with the current residue signal is largest. Simultaueously, the polynomial instantaneous frequency is estimated by connecting the linear frequency of the chirplet functions adopted in the current separation. Simulation experiment demonstrated that this method can separate the camponents of the multi-component polynamial phase signals effectively even in the low signal-to-noise ratio condition, and estimate its instantaneous frequency accurately. 展开更多
关键词 multi-scale chirplet base function multi-componentpolynomial phase signals instantaneous frequency signal- to noise ratio
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A Study on the Addictive Feature of Nonsuicidal Self-Injury in Adolescents With Depression Disorders and Its Correlation With Serum Beta-Endorphin Concentration and Neural Reward Responsiveness 认领 引用
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作者 Jie Li Xiaogang Zhu +4 位作者 Peiwen Zhang Yuxing Wang Jian Zhong Yiming Wang Lixia Yang 《iRADIOLOGY》 CSCD 2025年第6期456-464,共9页
Background:Nonsuicidal self-injury(NSSI)in adolescents with depression disorders often exhibits addictive patterns,potentially linked to serum beta-endorphin levels and neural reward responsiveness.Beta-endorphin,invo... Background:Nonsuicidal self-injury(NSSI)in adolescents with depression disorders often exhibits addictive patterns,potentially linked to serum beta-endorphin levels and neural reward responsiveness.Beta-endorphin,involved in reward processing,alongside dysregulated neural reward pathways,may reinforce self-injurious behaviors,highlighting the need to explore these mechanisms.Methods:Adolescents(aged 12-17 years)with depression disorders were divided into an NSSI group(21 subjects)and a control group(11 subjects)according to inclusion criteria.Serum beta-endorphin concentration was measured using the enzyme-linked immunosorbent assay method.The Addiction Factor Scale was used to assess addiction levels.Statistical analyses were con-ducted using SPSS 25.0.The oxygenated hemoglobin response signal was detected using functional near-infrared spectroscopy.Analyses were performed using NIRS_KIT 2.0.Results:Compared with the control group,the NSSI group exhibited lower serum beta-endorphin concentration.Additionally,85.7%of those in the NSSI group displayed addictive behaviors,and serum beta-endorphin concentration was negatively correlated with the Addiction Factor Scale score.The reward task activated channels 17,20,and 21(corresponding to the dorsolateral prefrontal cortex[PFC]and frontopolar PFC)in the gain condition and channels 20 and 21 in the loss condition.The oxygenated hemoglobin concentration of the differential waveform(Δ[oxy-Hb])of channel 12(corresponding to the frontopolar PFC)correlated positively with the Addiction Factor Scale score and negatively with the serum beta-endorphin concentration. 展开更多
关键词 adolescents with depression disorders beta-endorphin functional near-infrared spectroscopy neural reward responsiveness non-suicidal self-injury
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Reward Function Design Method for Long Episode Pursuit Tasks Under Polar Coordinate in Multi-Agent Reinforcement Learning 认领 引用 被引量：2
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作者 DONG Yubo CUI Tao +3 位作者 ZHOU Yufan SONG Xun ZHU Yue DONG Peng 《Journal of Shanghai Jiaotong university(Science)》 EI 2024年第4期646-655,共10页
Multi-agent reinforcement learning has recently been applied to solve pursuit problems.However,it suffers from a large number of time steps per training episode,thus always struggling to converge effectively,resulting... Multi-agent reinforcement learning has recently been applied to solve pursuit problems.However,it suffers from a large number of time steps per training episode,thus always struggling to converge effectively,resulting in low rewards and an inability for agents to learn strategies.This paper proposes a deep reinforcement learning(DRL)training method that employs an ensemble segmented multi-reward function design approach to address the convergence problem mentioned before.The ensemble reward function combines the advantages of two reward functions,which enhances the training effect of agents in long episode.Then,we eliminate the non-monotonic behavior in reward function introduced by the trigonometric functions in the traditional 2D polar coordinates observation representation.Experimental results demonstrate that this method outperforms the traditional single reward function mechanism in the pursuit scenario by enhancing agents’policy scores of the task.These ideas offer a solution to the convergence challenges faced by DRL models in long episode pursuit problems,leading to an improved model training performance. 展开更多
关键词 multi-agent reinforcement learning deep reinforcement learning(DRL) long episode reward function
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Multi-Scale Attention-Based Deep Neural Network for Brain Disease Diagnosis 认领 引用 被引量：1
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作者 Yin Liang Gaoxu Xu Sadaqat ur Rehman 《Computers, Materials & Continua》 SCIE EI 2022年第9期4645-4661,共17页
Whole brain functional connectivity(FC)patterns obtained from resting-state functional magnetic resonance imaging(rs-fMRI)have been widely used in the diagnosis of brain disorders such as autism spectrum disorder(ASD)... Whole brain functional connectivity(FC)patterns obtained from resting-state functional magnetic resonance imaging(rs-fMRI)have been widely used in the diagnosis of brain disorders such as autism spectrum disorder(ASD).Recently,an increasing number of studies have focused on employing deep learning techniques to analyze FC patterns for brain disease classification.However,the high dimensionality of the FC features and the interpretation of deep learning results are issues that need to be addressed in the FC-based brain disease classification.In this paper,we proposed a multi-scale attention-based deep neural network(MSA-DNN)model to classify FC patterns for the ASD diagnosis.The model was implemented by adding a flexible multi-scale attention(MSA)module to the auto-encoder based backbone DNN,which can extract multi-scale features of the FC patterns and change the level of attention for different FCs by continuous learning.Our model will reinforce the weights of important FC features while suppress the unimportant FCs to ensure the sparsity of the model weights and enhance the model interpretability.We performed systematic experiments on the large multi-sites ASD dataset with both ten-fold and leaveone-site-out cross-validations.Results showed that our model outperformed classical methods in brain disease classification and revealed robust intersite prediction performance.We also localized important FC features and brain regions associated with ASD classification.Overall,our study further promotes the biomarker detection and computer-aided classification for ASD diagnosis,and the proposed MSA module is flexible and easy to implement in other classification networks. 展开更多
关键词 Autism spectrum disorder diagnosis resting-state fMRI deep neural network functional connectivity multi-scale attention module
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Year-round multi-scale habitat selection by Crested Tit(Lophophanes cristatus)in lowland mixed forests(northern Italy) 认领 引用
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作者 Alessandro Berlusconi Alessio Martinoli +8 位作者 Lucas AWauters Giulia Tesoro Stefania Martini Erminio Clerici Gualtiero Guenzani Gabriele Pozzi Diego Rubolini Michelangelo Morganti Adriano Martinoli 《Avian Research》 SCIE CSCD 2022年第4期461-467,共7页
Determining how animals respond to resource availability across spatial and temporal extents is crucial to understand ecological processes underpinning habitat selection.Here,we used a multi-scale approach to study th... Determining how animals respond to resource availability across spatial and temporal extents is crucial to understand ecological processes underpinning habitat selection.Here,we used a multi-scale approach to study the year-round habitat selection of the Crested Tit(Lophophanes cristatus)in a semi-natural lowland woodland of northern Italy,analysing different habitat features at each scale.We performed Crested Tit censuses at three different spatial scales.At the macrohabitat scale,we used geolocalized observations of individuals to compute Manly's habitat selection index,based on a detailed land-use map of the study area.At the microhabitat scale,the trees features were compared between presence and absence locations.At the foraging habitat scale,individual foraging birds and their specific position on trees were recorded using focal animal sampling.Censuses were performed during both the breeding(March to May)and wintering(December to January)seasons.At the macrohabitat scale,the Crested Tits significantly selected pure and mixed pine forests and avoided woods of alien plant species,farmlands and urban areas.At the microhabitat scale,old pine woods with dense cover were selected,with no significant difference in the features of tree selection between the two phenological phases.At the foraging habitat scale,the species was observed spending more time foraging in the canopies than in the understorey,using mostly the portion of Scots Pine(Pinus sylvestris)canopies closer to the trunk in winter,while during the breeding period,the whole canopy was visited.Overall,breeding and wintering habitats largely overlapped in the Crested Tit.Based on our findings,lowland Crested Tits can be well defined as true habitat specialists:they are strictly related to some specific coniferous woodland features.Noteworthily,compared to other tit species,which normally show generalist habits during winter,the Crested Tit behaves as a habitat specialist also out of the breeding season.Our study stressed the importance of considering multi-scale(both spatial and phenological)habitat selection in birds. 展开更多
关键词 Crested tit Functional response Habitat selection Multi-scale approach Scots pine
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改进DDPG的磁浮控制研究 认领 引用 被引量：1
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作者 张振利 宋成林 +1 位作者 汪永壮 杨杰 《工程科学学报》 EI CAS CSCD 北大核心 2026年第2期422-435,共14页
针对部分传统磁浮控制算法依赖精确模型、适应性差的问题,提出一种基于强化学习的改进型深度确定性策略梯度(Improvement deep deterministic policy gradient, IDDPG)控制方法.首先,搭建电磁悬浮系统数学模型并分析其动态特性.其次,针... 针对部分传统磁浮控制算法依赖精确模型、适应性差的问题,提出一种基于强化学习的改进型深度确定性策略梯度(Improvement deep deterministic policy gradient, IDDPG)控制方法.首先,搭建电磁悬浮系统数学模型并分析其动态特性.其次,针对传统DDPG算法在电磁悬浮控制中的不足,设计一种分段式反比例奖励函数,以提升稳态精度和响应速度,并对DDPG控制流程进行分析及优化,以满足实际部署需求.最后,通过仿真与实验,对比分析电流环跟踪、奖励函数、训练步长以及模型变化对控制性能的影响.结果表明:采用分段式反比例奖励函数的IDDPG控制器在降低稳态误差和超调的同时,显著提升系统的响应速度,且优化后的控制流程适用于实际系统部署.此外,不同模型下使用相同参数稳态误差均低于5%,取得基本一致的控制效果,远优于滑模控制(Sliding mode control, SMC)的31%和比例–积分–微分控制(Proportional–Integral–Derivative control, PID)的12%,验证了IDDPG在不依赖精确模型情况下的良好适应性.同时,抗扰实验中,IDDPG相比PID超调减少51%,调节时间缩短49%,具有更强抗扰性. 展开更多
关键词 DDPG 奖励函数 控制指标 系统建模 磁浮系统 学习步长
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中国草畜平衡制度的结构优化与体系完善 认领 引用 被引量：1
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作者 陈宝山 姜贺天 +1 位作者 麻芦苇 丁梦茹 《自然资源学报》 CSSCI CSCD 北大核心 2026年第1期71-86,共16页
草畜平衡制度在抑制牧民超载放牧、保护草原生态平衡方面发挥着重要作用,但部分地区草畜矛盾、草地退化等问题依旧严峻。运用结构功能分析法对中国草畜平衡制度进行分析发现,草畜平衡制度的实施呈现出草原保护成效较为显著,通过法律手... 草畜平衡制度在抑制牧民超载放牧、保护草原生态平衡方面发挥着重要作用,但部分地区草畜矛盾、草地退化等问题依旧严峻。运用结构功能分析法对中国草畜平衡制度进行分析发现,草畜平衡制度的实施呈现出草原保护成效较为显著,通过法律手段明确制度运行的职、权、责关系的正功能,但也产生了限制放牧行为、抑制牧户权利、最终成为一种限权行为,以及影响牧户放牧收入、降低牧户守约积极性、产生负向激励的负功能。因果检视表明,草畜平衡规范结构断裂与制度结构配置不合理的外部结构障碍,核定周期过长、约束与激励失衡和监督监测制度局限的内部结构障碍,以及奖补混同抑制牧民积极性的内外部结构衔接障碍,共同制约了制度功能的发挥。鉴于此,应统筹草畜平衡与禁牧、休牧、轮牧、舍饲等制度,完善草畜平衡法规和制度体系,优化激励约束平衡、载畜量核定和监督监测制度,构建草畜平衡补奖与草原生态产品价值实现的衔接制度,破解制度结构障碍。 展开更多
关键词 草畜平衡制度 结构功能分析 奖补衔接 生态产品价值实现
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Multitype Game Optimisation:A Two-Stage Fine-Tuning Framework for Multi-Game Optimisation With Large Language Models 认领 引用
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作者 Xiali Li Jingshi Gu +3 位作者 Feifan He Yang Xiao Yuanli Jia Ping Lan 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2026年第3期739-753,共15页
Large language models(LLMs)have made remarkable advances in natural language processing,demonstrating great potential in modelling structured sequences.However,adapting these capabilities to machine gaming tasks such ... Large language models(LLMs)have made remarkable advances in natural language processing,demonstrating great potential in modelling structured sequences.However,adapting these capabilities to machine gaming tasks such as Go remains challenging due to limitations in strategy generalisation and optimisation efficiency.This paper presents multitype game optimisation(MyGO),a two-stage fine-tuning framework tailored for two-player perfect information board games,exploring the applicability of LLMs to nonlinguistic decision-making domains.In the supervised fine-tuning stage,we propose a unified structural encoding method,action semantic unit(ASU),which efficiently converts heterogeneous game records into discrete token sequences compatible with LLMs.In the reinforcement learning stage,we design TA-PPO(token-level adaptive proximal policy optimisation),an enhanced PPO-based algorithm to address the issue of sparse feedback commonly encountered in game reinforcement learning.Experimental results demonstrate that the fine-tuned models achieve superior or comparable performance to traditional game-playing algorithms in terms of strategy quality,rule generalisation and inference efficiency.This work provides a scalable paradigm for fine-tuning LLMs in complex decision-making tasks and lays a foundation for future research in game AI and generalisable strategy optimisation. 展开更多
关键词 computer game fine‐tuning large language models reinforcement learning reward function
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基于深度强化学习的永磁同步电机控制算法研究 认领 引用 被引量：1
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作者 范慧妍 王爽 《电机与控制应用》 2026年第3期269-278,共10页
【目的】深度强化学习(DRL)作为一种新兴的智能控制技术,在电机驱动系统控制领域展现出显著潜力。对此,本文研究并设计了一种先进的基于DRL的永磁同步电机(PMSM)驱动控制架构,旨在不依赖电机物理参数精确辨识的情况下,实现高精度、无模... 【目的】深度强化学习(DRL)作为一种新兴的智能控制技术,在电机驱动系统控制领域展现出显著潜力。对此,本文研究并设计了一种先进的基于DRL的永磁同步电机(PMSM)驱动控制架构,旨在不依赖电机物理参数精确辨识的情况下,实现高精度、无模型的鲁棒控制。【方法】本文将深度Q网络与有限控制集转矩控制结合,通过在线学习直接输出逆变器的开关状态,使智能体能够通过与电机环境的持续在线学习与交互,直接确定逆变器的最优开关状态。首先,设计了一个综合性多层次奖励函数以反映PMSM的复杂特性,同时兼顾了高保真转矩跟踪、定子电流幅值最小化以及系统整体能量效率最大化等多个优化目标。其次,为了弥补理论探索与实际安全需求之间的差距,建立了一种基于电流约束的新型安全保护与评估机制。该机制确保了DRL固有的随机探索过程不会导致系统过流或硬件损坏。最后,通过引入Q学习结构和自动化超参数优化方法,有效提高了算法的收敛性和控制性能。【结果】仿真结果表明,在训练400个回合后平均奖励值稳定于1附近,证明了算法优异的收敛性。所提算法能够精准跟踪转矩指令,在不同转速及负载阶跃工况下均保持了较快的响应速度与极小的稳态误差。通过合理的权重配置,系统有效实现了转矩精度与运行效率的平衡。此外,安全保护机制通过done信号实时截断高风险状态的预期收益,确保定子电流始终严格约束在安全阈值内,验证了模型在小样本场景下的稳健性。【结论】所提方案实现了无模型的高性能转矩控制,其引入的安全评估机制为强化学习在电力电子领域的应用提供了科学依据与预防性运维的新思路,为电机智能控制提供了新的研究方向。 展开更多
关键词 深度强化学习 永磁同步电机 有限控制集转矩控制 多层次奖励函数
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面向底盘运动性能优化的半主动悬架深度强化学习控制策略 认领 引用
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作者 陈国迎 王鑫煜 +3 位作者 张喜洲 王鹏 丛仕淇 高镇海 《汽车工程》 EI CSCD 北大核心 2026年第5期1091-1100,共10页
半主动悬架系统作为车辆底盘智能控制的核心部件,其阻尼特性动态调节能力直接决定了车辆行驶过程中的舒适性与操纵稳定性,对智能底盘运动性能优化起到至关重要的作用。传统算法在半主动悬架控制中对模型精度的依赖及车辆参数时变特性易... 半主动悬架系统作为车辆底盘智能控制的核心部件,其阻尼特性动态调节能力直接决定了车辆行驶过程中的舒适性与操纵稳定性,对智能底盘运动性能优化起到至关重要的作用。传统算法在半主动悬架控制中对模型精度的依赖及车辆参数时变特性易引发模型失配,削弱复杂工况下的控制鲁棒性;近年来推出的深度强化学习(DRL)算法在半主动悬架控制方面展现出巨大潜力。然而,DRL算法多聚焦于半主动悬架对乘坐舒适性的提升且算法脆弱收敛特性一直是该领域的主要挑战。本文提出了面向底盘运动性能优化的半主动悬架深度强化学习控制策略,设计了一个基于反正切函数的非参数奖励函数DQN算法(NRDQN),通过设计非参数奖励函数,控制策略能够较好应对系统不确定性,在保证训练收敛速度的同时兼顾车辆行驶时的操纵稳定性和驾驶舒适性。HIL试验验证结果表明,在混合路面激励的蛇行绕桩工况侧倾角均方根值抑制1.86%,乘坐舒适性提升了11.8%,NRDQN策略在不同行驶路面上和蛇行绕桩工况中均有良好的迁移性与鲁棒性。 展开更多
关键词 半主动悬架 深度强化学习 非参数奖励函数 多目标优化
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