期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到39,858篇文章
< 1 2 … 250 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Multi-Level Parallel Network for Brain Tumor Segmentation 认领 引用 被引量：2
1
作者 Juhong Tie Hui Peng 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第4期741-757,共17页
Accurate automatic segmentation of gliomas in various sub-regions,including peritumoral edema,necrotic core,and enhancing and non-enhancing tumor core from 3D multimodal MRI images,is challenging because of its highly... Accurate automatic segmentation of gliomas in various sub-regions,including peritumoral edema,necrotic core,and enhancing and non-enhancing tumor core from 3D multimodal MRI images,is challenging because of its highly heterogeneous appearance and shape.Deep convolution neural networks(CNNs)have recently improved glioma segmentation performance.However,extensive down-sampling such as pooling or stridden convolution in CNNs significantly decreases the initial image resolution,resulting in the loss of accurate spatial and object parts information,especially information on the small sub-region tumors,affecting segmentation performance.Hence,this paper proposes a novel multi-level parallel network comprising three different level parallel subnetworks to fully use low-level,mid-level,and high-level information and improve the performance of brain tumor segmentation.We also introduce the Combo loss function to address input class imbalance and false positives and negatives imbalance in deep learning.The proposed method is trained and validated on the BraTS 2020 training and validation dataset.On the validation dataset,ourmethod achieved a mean Dice score of 0.907,0.830,and 0.787 for the whole tumor,tumor core,and enhancing tumor core,respectively.Compared with state-of-the-art methods,the multi-level parallel network has achieved competitive results on the validation dataset. 展开更多
关键词 Convolution neural network brain tumor segmentation parallel network
暂未订购 下载PDF
Spatial morphology optimization for reconciling urban expansion with ecological integrity based on a multi-level ecological network framework 认领 引用 被引量：2
2
作者 LU Jie JIAO Sheng CHEN Xingli 《Journal of Geographical Sciences》 SCIE CSCD 2026年第2期399-420,共22页
Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecol... Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability. 展开更多
关键词 urban spatial morphology ecological network multi-level coupling scenarios simulation urban expansion
暂未订购 下载PDF
Parallel divergence with shared barriers,and niche separation between two sympatric avian species groups 认领 引用 被引量：1
3
作者 Lei Wu Huan Wang +10 位作者 Yanzhu Ji Ali Haghani Yan Hao Dezhi Zhang Gang Song Yalin Cheng Martin Päckert Jochen Martens Chenxi Jia Per Alström Fumin Lei 《Journal of Systematics and Evolution》 SCIE CSCD 2026年第1期77-94,共18页
Geographic barriers and geological historical events may play pivotal roles in driving allopatric divergence among closely related species.Here,we investigate the genomic divergence patterns and ecological niche separ... Geographic barriers and geological historical events may play pivotal roles in driving allopatric divergence among closely related species.Here,we investigate the genomic divergence patterns and ecological niche separation of the Willow Tit Poecile montanus and the Marsh Tit P.palustris species groups in China,and their ecological niche separation across East Asia.Through comprehensive genomic sequencing,population genomic analysis,and integration of public occurrence data,we unveil striking parallels in the geographic divergence patterns between these two species groups.Notably,both species exhibit multiple divergent lineages in China,with similar spatial distributions of geneflow barriers.Furthermore,our analysis reveals unique evolutionary histories in the southwestern clades of both species groups,highlighting the intricate interplay between historical distribution dynamics,ecological preferences,and genetic divergence.Our study significantly enhances our understanding of the processes underlying the diversification of closely related widespread species within the framework of shared geographical constraints,and stresses the need for a taxonomic revision. 展开更多
关键词 biogeography East Asia Marsh Tit parallel divergence Willow Tit
Nonlinear coupling mechanism of quasi-zero-stiffness units in multi-level structures 认领 引用
4
作者 Shaokun YANG Xingxing SHI +2 位作者 Xingzhong WANG Jiuhui WU Fuyin MA 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2026年第6期1215-1240,共26页
Multilayer structures composed of quasi-zero-stiffness(QZS)units exhibit mechanical characteristics distinct from those of a single unit,and their behaviors are governed by the coupling mechanism between the QZS units... Multilayer structures composed of quasi-zero-stiffness(QZS)units exhibit mechanical characteristics distinct from those of a single unit,and their behaviors are governed by the coupling mechanism between the QZS units.This paper introduces the coupling coefficient to quantitatively describe this mechanism,classifying the system into strongly coupled and weakly coupled states.Through theoretical analysis,numerical simulation,and experimental testing,the static and dynamic responses under different coupling states are comparatively investigated.The results show that in the strongly coupled system,the deformation behavior of each QZS unit shows high consistency,leading to a wider QZS region,weaker nonlinear characteristics,and stronger dynamic response.In the weakly coupled systems,the low degree of deformation coordinations among the units results in different QZS regions,enabling low-frequency vibration isolation under varying loads.The analytical approach of the coupling mechanisms and the static and dynamic response behaviors generated by the two coupling mechanisms provide guidance for the structural design of multifunctional and highly adaptable multi-level QZS metamaterials. 展开更多
关键词 multi-level structure coupling mechanism strong coupling weak coupling deformation coordination
暂未订购 下载PDF
FTCSEM—A FORTRAN-based parallelized 1D CSEM forward and inversion program for arbitrary source-receiver geometry 认领 引用
5
作者 Wei-ying Chen Si-xu Han +2 位作者 Wan-ting Song Yu-lian Zhu Zheng Liu 《Applied Geophysics》 SCIE CSCD 2026年第2期693-709,870,共17页
This study introduces FTCSEM,a FORTRAN-based,parallelized one-dimensional controlledsource electromagnetic(CSEM)forward modeling and inversion software capable of accommodating arbitrary source-receiver confi guration... This study introduces FTCSEM,a FORTRAN-based,parallelized one-dimensional controlledsource electromagnetic(CSEM)forward modeling and inversion software capable of accommodating arbitrary source-receiver confi gurations.In comparison to existing one-dimensional CSEM tools,FTCSEM incorporates several signifi cant enhancements:it supports transmitters of diverse shapes,quantities,and spatial locations;permits receivers to be positioned flexibly on the surface,subsurface,or in the atmosphere;facilitates simulations and inversions in both frequency and time domains;integrates an adaptive regularized inversion algorithm with multiple model constraints;and leverages GPU-accelerated parallel computing to attain high computational efficiency.Validation through numerical experiments and field data inversion confirms the program’s accuracy and practical applicability.The findings indicate that FTCSEM performs robustly in complex geoelectric environments,multi-source and multi-receiver arrangements,as well as multi-component joint inversion scenarios,thereby offering a versatile and powerful tool for advancing CSEM research and applications. 展开更多
关键词 CSEM forward modeling regularized inversion parallel computing program
暂未订购 下载PDF
Advancements and theoretical foundations of cable-driven parallel robots:A comprehensive overview 认领 引用
6
作者 Kamran Joyo Han Yuan +2 位作者 Jun Wu Wenfu Xu Honghao Yue 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第3期280-305,共26页
Parallel robotic mechanisms using cables instead of rigid limbs are termed cable-driven parallel robots(CDPRs).Electric motors and pulley mechanisms actuate cables to provide motion for an end-effector in a cable robo... Parallel robotic mechanisms using cables instead of rigid limbs are termed cable-driven parallel robots(CDPRs).Electric motors and pulley mechanisms actuate cables to provide motion for an end-effector in a cable robot.Consequently,CDPRs have emerged as indispensable tools across a spectrum of industrial and technological domains,including astronomy,aerospace,logistics,simulators,and rehabilitation.Their inherent compatibility with the evolving concept of rigid-flexible fusion places CDPRs at the forefront of cutting-edge robotics research.This comprehensive paper aims to consolidate the core theories and advancements underpinning CDPRs,en-compassing key aspects such as configuration design,cable-force distribution,workspace and stiffness analysis,performance evaluation,optimisation techniques,and motion control.We provide in-depth insights into kine-matic modelling,workspace exploration,and cable-force solutions.Furthermore,the paper delves into the in-tricacies of stiffness and dynamic modelling,presenting a range of analytical methods to elucidate their effects on CDPR performance.Addressing reliability concerns and developing a unified control framework are identified as essential in ensuring the practical deployment of CDPRs in real-world scenarios.This research paper offers a comprehensive overview of the theories and advancements in CDPRs,identifying critical areas for further re-search and development to unlock the full potential of these versatile and high-performance robotic systems. 展开更多
关键词 Cable-driven parallel robots Optimisation Path generation Statics Machine learning
暂未订购 下载PDF
Optimal design of a novel dual-axis parallel solar tracker 认领 引用
7
作者 Bin Zhu Liping Wang +2 位作者 Jun Wu Hengchun Cui Yanling Tian 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第2期167-179,共13页
Being renewable and readily available,solar energy has gained significant attention in addressing the global energy crisis and climate change.The efficiency of solar-energy harvesting using a concentrator depends on t... Being renewable and readily available,solar energy has gained significant attention in addressing the global energy crisis and climate change.The efficiency of solar-energy harvesting using a concentrator depends on the angle between the incident sunlight and the solar concentrator.Therefore,a solar-energy collection system equipped with a solar tracker that follows the apparent motion of the sun offers the highest collection efficiency.In this study,a novel solar tracker with a parallel mechanism is proposed based on the line graph method.The proposed parallel solar tracker(PST) features a main column with passive movements and two UPU chains that share a common constraint.This design enhances the rotational workspace,stiffness,and load-bearing capacity of the system.To solve the forward kinematics problem of the PST efficiently and accurately,a geometric elimination method is employed,converting the three-dimensional kinematics into a simpler planar problem.This allows the forward kinematics problem to be solved analytically using planar equations.By considering key performance indices,such as the effective workspace,transmission,and manipulability,the structural parameters of the PST are optimized in two steps,thereby identifying the optimal region in the design space.Finally,the computational efficiency and accuracy of both the forward and inverse kinematic solutions for the PST with optimized structural parameters are validated,demonstrating their potential for use in real-time control systems.The proposed novel solar tracker has high stiffness and load-bearing capacity.The study provides a solid foundation for improving the efficiency of solar energy utilization. 展开更多
关键词 Solar tracker Parallel mechanism Forward kinematics Effective workspace Transmissibility Manipulability
暂未订购 下载PDF
Impact toughness,crack initiation and propagation mechanism of Ti6422 alloy with multi-level lamellar microstructure 认领 引用
8
作者 Jie Shen Zhihao Zhang Jianxin Xie 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2026年第2期595-609,共15页
The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.... The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and αp lamellae,as well as nanoscale αs phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the αp lamella content,reduced the αs phase content,expanded theαcolonies and αp lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm2.Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the αs phase content and a growth in the thickness of the αp lamella and αs phase.The impact toughness increased significantly with these changes.Samples with high αp lamellae content or large αs phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the αp lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and αp lamellae continuously deflect the crack propagation direction,inhibiting crack propagation. 展开更多
关键词 novel titanium alloy multi-level lamellar microstructure impact toughness crack initiation and propagation
暂未订购 下载PDF
The three-dimensional meshfree numerical manifold method based on parallel computing 认领 引用
9
作者 Keqin Zhang Wei Wu +2 位作者 Danfeng Zhang Yanfei Kang Hehua Zhu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第2期360-371,共12页
The numerical manifold method,extensively utilized in numerical computations,faces significant challenges in generating complex manifold elements,particularly for three-dimensional applications.To overcome this challe... The numerical manifold method,extensively utilized in numerical computations,faces significant challenges in generating complex manifold elements,particularly for three-dimensional applications.To overcome this challenge,the meshfree numerical manifold method is developed by integrating the moving least-squares method into the numerical manifold method,effectively bypassing the need for meshing complex geometric objects.However,the implementation of the moving least-squares method introduces computational efficiency issues.To mitigate these,parallel computing methods have been incorporated,resulting in a tenfold increase in the speed of assembling the stiffness matrix with central processing unit parallelism,and a twentyfold increase with graphics processing unit parallelism.The static mechanical system equations for the meshfree numerical manifold method are derived using the Galerkin method.The method’s effectiveness and accuracy are then validated through a series of numerical experiments.The experiments demonstrated that the meshfree numerical manifold method achieves a high precision with minimal nodes and integration points.Additionally,positioning nodes outside the domain significantly improves computational accuracy at the boundaries. 展开更多
关键词 Meshfree numerical manifold method Three-dimensional computation Parallel computation Elastostatics Moving least-squares
暂未订购 下载PDF
A high-performance parallel algorithm based on problem independent machine learning(PIML)for large-scale topology optimization 认领 引用
10
作者 Xinyu Ma Mengcheng Huang +4 位作者 Zongliang Du Yilin Guo Chang Liu Yue Mei Xu Guo 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第3期197-213,共17页
Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integra... Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integrated with topology optimization,achieving significant attention and progress in large-scale problems.This work aims to investigate how much benefit can be obtained by combining parallel computing and machine learning techniques to enhance the efficiency of large-scale topology optimization algorithms.Accordingly,a parallel problem independent machine learning(PIML)-enhanced topology optimization method is proposed.The PIML model substantially reduces the dimension of the condensed stiffness matrix and its computational cost,and parallel computing reduces the workload per process and enables the application of a parallel multigrid solver.Besides,several techniques,such as matrix-free implementation,direct condensation of uniform coarse elements,and adjusting computational resource limits,have been developed to enhance computational efficiency.The weak scaling efficiency,strong scaling speedup,and maximum achievable efficiency of the proposed method are validated across multiple numerical examples,showing significant improvement in the tractable problem size and solution efficiency compared to traditional topology optimization algorithms. 展开更多
关键词 Topology optimization Large-scale Problem independent machine learning(PIML) Parallel computing
暂未订购 下载PDF
A 32‑channel charge‑sensitive amplifier for delay‑line readout of parallel plate avalanche counter array 认领 引用
11
作者 Yue‑Zhao Zhang Peng Ma +8 位作者 Zhuang‑Yu Lin Zhen‑Fei Tan Xing‑Chi Han Chen Liu Shuo Wang Da‑Peng Sun Zhi‑Quan Li En‑Hong Wang Shou‑Yu Wang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2026年第1期164-179,共16页
A 32-channel charge-sensitive amplifier(CSA)is designed for fast timing in the delay-line readout of a parallel plate avalanche counter(PPAC)array.It is realized on a PCB with operational amplifiers and other discrete... A 32-channel charge-sensitive amplifier(CSA)is designed for fast timing in the delay-line readout of a parallel plate avalanche counter(PPAC)array.It is realized on a PCB with operational amplifiers and other discrete components.Each channel consists of an integrator,a pole-zero cancellation net,and a linear amplification stage,which can be adapted to accommodate either positive or negative input signals.The RMS equivalent input noise charges are 3.3 fC,the conversion gains are approximately±2 mV∕fC,and the intrinsic time resolution reaches 32 ps.In the prototype PPAC application,the CSA performs as well as the commercial FTA820A amplifier,providing a position resolution as good as 0.17 mm,and exhibiting reliable stability during several hours of continuous data acquisition. 展开更多
关键词 Charge-sensitive amplifier Fast timing Parallel plate avalanche counter Delay-line Discrete components
暂未订购 下载PDF
Stiffness evaluation and experimental test of a novel redundantly actuated parallel machining robot 认领 引用
12
作者 Hanliang Fang Jian Wang +2 位作者 Shuyi Ge Fufu Yang Jun Zhang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第1期413-422,共10页
Parallel machining robot is a new type of robotized equipment for high-efficiency machining structural com-ponents with complex geometries.Terminal rigidity is of great importance index for such type of equipment,whic... Parallel machining robot is a new type of robotized equipment for high-efficiency machining structural com-ponents with complex geometries.Terminal rigidity is of great importance index for such type of equipment,which affects their load capacity and working accuracy.Before a parallel machining robot can be used for heavy-load and high-efficiency machining,its terminal rigidity should be evaluated systematically.The present study is to quantitatively reveal the stiffness properties of a previously invented Z4 redundantly actuated parallel ma-chining robot(RAPMR).For this purpose,two critical issues,i.e.,stiffness modelling and index construction,are clarified to carry out stiffness evaluation of the Z4 RAPMR.Firstly,drawing on the screw theory,a semi-analytic stiffness model of the proposed RAPMR is established at a component level.Secondly,a set of virtual work-based stiffness indices is constructed to evaluate the terminal rigidity of parallel robots.Those indices have a consistent physical unit in describing linear and angular terminal rigidity.With these indices,the local and the global stiffness performance of the Z4 RAPMR are predicted.Thirdly,a laboratory prototype of the proposed RAPMR is fabricated.And the experimental test is performed to verify the correctness of the established stiffness model.The present work is expected to provide fundamental information for further light-weight design and rigidity enhancement. 展开更多
关键词 Parallel machining robot Redundantly actuated Terminal rigidity Stiffness model Experimental test
暂未订购 下载PDF
Symmetry Breaking in Parallel 1-K Sorption Coolers and Passive Suppression Strategy 认领 引用
13
作者 Lihao Lu Yan Lu +2 位作者 Zhenhua Jiang Shaoshuai Liu Yinong Wu 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第3期105-122,共18页
Sub-Kelvin cooling technology is a critical prerequisite for high-sensitivity detection in deep space exploration and quantum computing.Operating identical sorption coolers in parallel is a common engineering approach... Sub-Kelvin cooling technology is a critical prerequisite for high-sensitivity detection in deep space exploration and quantum computing.Operating identical sorption coolers in parallel is a common engineering approach to enhance cooling capacity and extend hold time for these cryogenic platforms.However,this study reports an unexpected"symmetry breaking"phenomenon observed in a parallel Helium-4 sorption cooling system where the cold heads are connected via Oxygen-Free High Thermal Conductivity(OFHC)copper linkages.Instead of the expected uniform load sharing,the system spontaneously evolves into an asymmetric"quasi-series"operational mode.In this state,one cooler preferentially consumes its liquid helium inventory while the other remains dormant,significantly reducing system efficiency.To elucidate the underlying physics,a transient thermal-fluidic resistance network model was developed and validated against experimental data obtained from a dual-cooler test rig pre-cooled by a G-M cryocooler.Theoretical analysis reveals that this thermal locking originates from a positive feedback loop driven by the temperature-dependent thermal conductivity of the copper straps.Experimental results further demonstrate that system stability degrades significantly with increasing thermal load,with the synchronization ratio dropping from 75.3%at 0 mW to 51.3%at 3 mW.This indicates that at higher temperatures,the destabilizing gain of the thermal link overwhelms the restoring stiffness of the sorption mechanism.To address this intrinsic instability,a passive suppression strategy using a series"Ballast Thermal Resistance"is proposed.Numerical optimization identifies a critical resistance value of approximately 10 K/W,which effectively dampens the positive feedback and restores the synchronization ratio to over 95%with a negligible thermal penalty of less than 20 mK.These findings provide a theoretical basis and practical design guidelines for the stabilization of multi-cooler cryogenic networks. 展开更多
关键词 Sorption cooler parallel system symmetry breaking thermal locking passive stabilization ballast thermal resistance
暂未订购 下载PDF
A Deep Reinforcement Learning-Based Partitioning Method for Power System Parallel Restoration 认领 引用
14
作者 Changcheng Li Weimeng Chang +1 位作者 Dahai Zhang Jinghan He 《Energy Engineering》 EI 2026年第1期243-264,共22页
Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision... Effective partitioning is crucial for enabling parallel restoration of power systems after blackouts.This paper proposes a novel partitioning method based on deep reinforcement learning.First,the partitioning decision process is formulated as a Markov decision process(MDP)model to maximize the modularity.Corresponding key partitioning constraints on parallel restoration are considered.Second,based on the partitioning objective and constraints,the reward function of the partitioning MDP model is set by adopting a relative deviation normalization scheme to reduce mutual interference between the reward and penalty in the reward function.The soft bonus scaling mechanism is introduced to mitigate overestimation caused by abrupt jumps in the reward.Then,the deep Q network method is applied to solve the partitioning MDP model and generate partitioning schemes.Two experience replay buffers are employed to speed up the training process of the method.Finally,case studies on the IEEE 39-bus test system demonstrate that the proposed method can generate a high-modularity partitioning result that meets all key partitioning constraints,thereby improving the parallelism and reliability of the restoration process.Moreover,simulation results demonstrate that an appropriate discount factor is crucial for ensuring both the convergence speed and the stability of the partitioning training. 展开更多
关键词 Partitioning method parallel restoration deep reinforcement learning experience replay buffer partitioning modularity
暂未订购 下载PDF
A Competitive Parallel Animated Oat Optimization Algorithm for Reversible Digital Watermarking 认领 引用
15
作者 Shu-Chuan Chu Libin Fu Jeng-Shyang Pan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第7期1209-1238,共30页
The Animated Oat Optimization Algorithm(AOO)is a novel evolutionary algorithm inspired by the behavior of animated oats.This paper proposes a Competitive Parallel Animated Oat Optimization Algorithm(CPAOO)comprising t... The Animated Oat Optimization Algorithm(AOO)is a novel evolutionary algorithm inspired by the behavior of animated oats.This paper proposes a Competitive Parallel Animated Oat Optimization Algorithm(CPAOO)comprising two components.First,a parallel strategy is employed in which inter-subpopulation communication is triggered at predefined iteration thresholds to balance exploration and exploitation.Second,a grouped competition strategy with incentive mechanisms is introduced,enabling the prioritized evolution of superior individuals to enhance the algorithm’s efficiency.Furthermore,building on the Prediction Error Expansion(PEE)algorithm,this paper proposes a Dual-Layer PEE(DLPEE)algorithm for reversible digital watermarking.Based on differences in pixel values around embedding points,image blocks are classified as either smooth or textured regions.The CPAOO algorithm is used to optimize the weights of the pixel predictor and to prioritize embedding secret information in smooth blocks.This approach enhances both the embedding capacity and the invisibility of the watermarked data.Experimental results demonstrate that the proposed methods achieve satisfactory performance. 展开更多
关键词 Evolutionary algorithm parallel strategy communication strategy grouped competition strategy reversible digital watermarking
暂未订购 下载PDF
An Eulerian-Lagrangian parallel algorithm for simulation of particle-laden turbulent flows 认领 引用 被引量：1
16
作者 Harshal P.Mahamure Deekshith I.Poojary +1 位作者 Vagesh D.Narasimhamurthy Lihao Zhao 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第1期15-34,共20页
This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in ... This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance. 展开更多
关键词 DNS Eulerian-Lagrangian Particle tracking algorithm Point-particle Parallel software
暂未订购 下载PDF
Research on Ultra-Short-Term Photovoltaic Power Forecasting Based on Parallel Architecture TCN-BiLSTM with Temporal-Spatial Attention Mechanism 认领 引用 被引量：1
17
作者 Hongbo Sun Xingyu Jiang +4 位作者 Wenyao Sun Yi Zhao Jifeng Cheng Xiaoyi Qian Guo Wang 《Energy Engineering》 EI 2026年第4期303-320,共18页
The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback ... The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency. 展开更多
关键词 Ultra-short-term forecasting temporal convolutional network bidirectional long short-term memory parallel dual-stream architecture temporal-spatial attention SHAP contribution analysis
暂未订购 下载PDF
Data-driven corrosion assessment of magnesium alloys:A multi-level graph attention network for quantitative hydrogen-evolution prediction 认领 引用
18
作者 Xinqian Zhao Xu Qin +6 位作者 Shouxin Xia Jiabao Long Dabiao Xia Huabao Yang Di Zhao Qinghang Wang Daolun Chen 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2026年第5期527-544,共18页
Magnesium(Mg)alloys are highly valued in aerospace,biomedical and other fields due to their high specific strength.However,nonuniform corrosion failure during service remains a core challenge that restricts their engi... Magnesium(Mg)alloys are highly valued in aerospace,biomedical and other fields due to their high specific strength.However,nonuniform corrosion failure during service remains a core challenge that restricts their engineering applications.Traditional corrosion kinetics models fail to accurately elucidate the cross-scale synergy mechanism between microstructure and macroscopic corrosion behavior.In this study,based on 13 kinds of Mg alloys,20 sets of 100-h hydrogen evolution curves,and characterization data from scanning electron microscopy(SEM)and electron backscatter diffraction(EBSD)information,a multi-level corrosion kinetics database was constructed,covering physicochemical parameters,micro-grain topological structures and second phase features,as well as macroscopic statistical characteristics and temporal dimension.Through machine learning algorithms,key corrosion driving factors were identified,and a multi-level graph attention network modeling framework was proposed,where the grains and grain boundaries were constructed as a graph structure,and the hierarchical interaction modeling between microstructure and corrosion kinetics was realized by combining the attention mechanism.The model has been validated in a new Mg alloy dataset for its predictive capability across compositional systems.This work provides a new computational paradigm and significantly enhances the predictability and efficiency of corrosion-resistant Mg alloy design. 展开更多
关键词 Magnesium alloy Multi-level graph attention network Quantitative hydrogen evolution prediction Microstructure-level corrosion mechanism
暂未订购 下载PDF
A Subdomain-Based GPU Parallel Scheme for Accelerating Perdynamics Modeling with Reduced Graphics Memory 认领 引用
19
作者 Zuokun Yang Jun Li +1 位作者 Xin Lai Lisheng Liu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期256-285,共30页
Peridynamics(PD)demonstrates unique advantages in addressing fracture problems,however,its nonlocality and meshfree discretization result in high computational and storage costs.Moreover,in its engineering application... Peridynamics(PD)demonstrates unique advantages in addressing fracture problems,however,its nonlocality and meshfree discretization result in high computational and storage costs.Moreover,in its engineering applications,the computational scale of classical GPU parallel schemes is often limited by the finite graphics memory of GPU devices.In the present study,we develop an efficient particle information management strategy based on the cell-linked list method and on this basis propose a subdomain-based GPU parallel scheme,which exhibits outstanding acceleration performance in specific compute kernels while significantly reducing graphics memory usage.Compared to the classical parallel scheme,the cell-linked list method facilitates efficient management of particle information within subdomains,enabling the proposed parallel scheme to effectively reduce graphics memory usage by optimizing the size and number of subdomains while significantly improving the speed of neighbor search.As demonstrated in PD examples,the proposed parallel scheme enhances the neighbor search efficiency dramatically and achieves a significant speedup relative to serial programs.For instance,without considering the time of data transmission,the proposed scheme achieves a remarkable speedup of nearly 1076.8×in one test case,due to its excellent computational efficiency in the neighbor search.Additionally,for 2D and 3D PD models with tens of millions of particles,the graphics memory usage can be reduced up to 83.6%and 85.9%,respectively.Therefore,this subdomain-based GPU parallel scheme effectively avoids graphics memory shortages while significantly improving the computational efficiency,providing new insights into studying more complex large-scale problems. 展开更多
关键词 Peridynamics GPU CUDA parallel computing cell-linked list
暂未订购 下载PDF
A Control-based Transition Reinforced Optimization Process for Multi-level Threshold Image Segmentation 认领 引用
20
作者 Wei Wang Peiying Zhang +5 位作者 Saleh Ali Alomari Raed Abu Zitar Aseel Smerat Mohamed Sharaf Absalom E.Ezugwu Laith Abualigah 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第2期1061-1087,共27页
In this study,we present a novel approach to multi-threshold image segmentation using an adaptive method that combines the Ebola Optimization Search Algorithm(EOSA)with the Aquila Optimizer,termed the Integrated Enhan... In this study,we present a novel approach to multi-threshold image segmentation using an adaptive method that combines the Ebola Optimization Search Algorithm(EOSA)with the Aquila Optimizer,termed the Integrated Enhanced Ebola Optimization Search Algorithm(IEOSA).Our approach leverages this integration to produce high-quality segmented images.The IEOSA method introduces two distinct optimization mechanisms to identify optimal solutions.By blending the randomness of the Aquila Optimizer with the capabilities of EOSA,we enhance the exploration potential of the algorithm.Additionally,we incorporate a self-transition learning system within the IEOSA to further boost its performance.To tackle multi-level threshold image segmentation,we apply Kapur’s entropy between-class variance within the IEOSA framework.Our findings show that the IEOSA-based techniques outperform other comparable methods,offering faster convergence and more stable segmentation results.Through comparative analysis using standard test images,we demonstrate that IEOSA achieves higher solution accuracy than other methods.Ultimately,the proposed IEOSA methodologies effectively address multi-level threshold image segmentation challenges,accurately segmenting even the minor errors that are often overlooked in high-resolution images. 展开更多
关键词 Ebola optimization search algorithm(EOSA) Aquila optimizer(AO) Multi-level threshold Image segmentation Transition mechanism
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 250 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈