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FishTracker:An Efficient Multi-Object Tracking Algorithm for Fish Monitoring in a RAS Environment 认领 引用
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作者 Yuqiang Wu Zhao Ji +4 位作者 Guanqi You Zihan Zhang Chaoping Lu Huanliang Xu Zhaoyu Zhai 《Computers, Materials & Continua》 SCIE EI 2026年第2期805-826,共22页
Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the ... Understanding fish movement trajectories in aquaculture is essential for practical applications,such as disease warning,feeding optimization,and breeding management.These trajectories reveal key information about the fish’s behavior,health,and environmental adaptability.However,when multi-object tracking(MOT)algorithms are applied to the high-density aquaculture environment,occlusion and overlapping among fish may result in missed detections,false detections,and identity switching problems,which limit the tracking accuracy.To address these issues,this paper proposes FishTracker,a MOT algorithm,by utilizing a Tracking-by-Detection framework.First,the neck part of the YOLOv8 model is enhanced by introducing a Multi-Scale Dilated Attention(MSDA)module to improve object localization and classification confidence.Second,an Adaptive Kalman Filter(AKF)is employed in the tracking phase to dynamically adjust motion prediction parameters,thereby overcoming target adhesion and nonlinear motion in complex scenarios.Experimental results show that FishTracker achieves a multi-object tracking accuracy(MOTA)of 93.22% and 87.24% in bright and dark illumination conditions,respectively.Further validation in a real aquaculture scenario reveal that FishTracker achieves aMOTA of 76.70%,which is 5.34% higher than the baselinemodel.The higher order tracking accuracy(HOTA)reaches 50.5%,which is 3.4% higher than the benchmark.In conclusion,FishTracker can provide reliable technical support for accurate tracking and behavioral analysis of high-density fish populations. 展开更多
关键词 Aquaculture multi-object tracking YOLOv8 adaptive Kalman filter attention mechanism
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Robust Multi-Object Fish Tracking in Dynamic Aquatic Environments via Attention-Enhanced YOLOv8 and LSTM-Based Trajectory Prediction 认领 引用
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作者 Feng-Cheng Lin Bo-Chiao Jan Hui-An Wu 《Computers, Materials & Continua》 SCIE EI 2026年第7期1577-1600,共24页
With the increasing refinement of ornamental fish culture,understanding fish behavioral patterns has become critical.Fish movements not only reflect daily activity ranges but also reveal responses to environmental cha... With the increasing refinement of ornamental fish culture,understanding fish behavioral patterns has become critical.Fish movements not only reflect daily activity ranges but also reveal responses to environmental changes such as water currents and obstacles.However,traditional manual observation is limited by manpower and time,making it difficult to record fish behaviors over long periods stably.Existing automated tracking techniques often suffer from ID switches and track interruptions caused by rapid fish movement,occlusions,or intermingling,which in turn degrade the reliability of subsequent analyses.This paper proposes a deep learning-based multi-object fish tracking system that integrates YOLOv8n for object detection and employs an IoU matching criterion to associate detections across consecutive frames,thereby maintaining object ID continuity.To further reduce ID loss under rapid motion and partial occlusion,a multiple-LSTM prediction model is introduced as a temporal compensation mechanism,thereby improving timing stability and track continuity.Moreover,considering disturbances in the experimental field(e.g.,water disturbance and water current interference)that can blur fish body edges and fine details,an attention-enhanced detector,YOLOv8-CS(Convolutional Block Attention Module and Squeeze-and-Excitation),is developed by embedding CBAM and SE modules into the YOLOv8 architecture to enhance detection accuracy in dynamic waters.Experimental results demonstrate that the proposed system effectively increases the Multiple Object Tracking Accuracy(MOTA)to 77.23%and significantly reduces ID switches to 42.5,ensuring more robust and continuous trajectory tracking compared to benchmark methods.This system provides a highly reliable tool for automated behavior analysis in complex and dynamic aquatic environments. 展开更多
关键词 LSTM trajectory prediction multi-object tracking YOLOv8-CS attention mechanism
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MDGAN-DIFI: Multi-Object Tracking for USVs Based on Deep Iterative Frame Interpolation and Motion Deblurring Using GAN Model 认领 引用
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作者 Manh-Tuan Ha Nhu-Nghia Bui +1 位作者 Dinh-Quy Vu Thai-Viet Dang 《Computers, Materials & Continua》 SCIE EI 2026年第6期697-720,共24页
In the realm of unmanned surface vehicle(USV)operations,leveraging environmental factors to enhance situational awareness has garnered significant academic attention.Developing vision systems for USVs presents conside... In the realm of unmanned surface vehicle(USV)operations,leveraging environmental factors to enhance situational awareness has garnered significant academic attention.Developing vision systems for USVs presents considerable challenges,mainly due to variable observational conditions and angular vibrations caused by hydrodynamic forces.The paper proposed a novel MDGAN-DIFI network for end-to-end multi-object tracking(MOT),specifically designed for camera systems mounted on USVs.Beyond enhancing traditional MOT models,the proposed MDGAN-DIFI includes preprocessing modules designed to enhance the efficiency of processing input signal quality.Initially,a Deep Iterative Frame Interpolation(DIFI)module is used to stabilize frames in the spatiotemporal domain.Next,an enhanced generative adversarial network(GAN)model is applied to reduce motion blur affecting objects within the field of view.Finally,a YOLO-CSSA architecture combines dual infrared(IR)and RGB data streams to maintain consistent performance across diverse environmental conditions.By synthesizing intermediate frames and restoring blurred details,the framework seeks to stabilize object motion trajectories and recover distinctive appearance features prior to tracking.This approach directly tackles the main causes of tracking failure in maritime environments,such as motion discontinuities and visual degradation.Experimental results demonstrate that the proposed approach outperforms conventional methods in multi-object tracking on USVs,achieving a maximum accuracy(MOTA)of 47.0%and an IDF1 score of 50.1%under challenging operational conditions.Consequently,the proposed multi-object tracking network provides a more robust foundation for subsequent detection and data association processes. 展开更多
关键词 Multi-object tracking unmanned surface vehicles deep interactive frame interpolation motion blur generative adversarial networks(GAN)
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TopoEKF:From State-Space Estimation to Topological Signatures for Enhanced Multi-Object Tracking and Anomaly Detection in UAVs 认领 引用
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作者 Rabia Kıratlı Hatice Unlu Eroğlu Alperen Eroğlu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第6期860-908,共49页
Reliable multi-object detection and tracking play a critical role in Unmanned Aerial Vehicles-based aerial surveillance applications operating under challenging real-world conditions.This study presents a mathematical... Reliable multi-object detection and tracking play a critical role in Unmanned Aerial Vehicles-based aerial surveillance applications operating under challenging real-world conditions.This study presents a mathematically grounded,model-driven tracking framework named TopoEKF,which integrates an enhanced Adaptive Extended Kalman Filter with Topological Data Analysis to improve both tracking robustness and anomaly detection performance.Unlike prior approaches that primarily focus on refining object detection architectures,this work emphasizes the predictive power of iterative Bayesian filtering,optimal state estimation,and adaptive error minimization within a unified mathematical framework.The proposed system employs a carefully optimized YOLOvl2 detector to provide accurate object location priors,followed by a formally defined discrete-time linear Gaussian tracking model.The Adaptive EKF is leveraged to handle nonlinearities arising from the projection of three-dimensional object motion onto the two-dimensional image plane through local linearization.To further enhance robustness under low resolution,large object-to-image distances,frequent occlusions,and environmental noise,TopoEKF introduces adaptive noise covariance modeling driven by measurement confidence,occlusion status,and topological feedback.Persistent homology is applied to EKF-filtered trajectories to extract topological signatures that characterize the global structure of object motion.These features are transformed into fixed-dimensional representations and processed by an unsupervised Isolation Forest classifier for trajectory-level anomaly detection.Experimental evaluations are conducted on a challenging hybrid dataset combining scenarios from COCO,VisDrone,UAVDT,Road_Anomaly_Dataset,and DoTA benchmarks.Quantitative results demonstrate that TopoEKF improves Multi-Object Tracking Accuracy from 72.8%to 76.3%and reduces identity switches by approximately 34%compared to a standard EKF baseline.The enhanced EKF achieves up to 20%higher robustness in highly noisy and indoor environments while maintaining realtime performance at 28.5 frames per second on resource-constrained embedded platforms.In the anomaly detection stage,the integration of persistent homology-based features improves the F1-score from 66%to 84%,with substantial gains in both precision and recall.Overall,the proposed approach highlights the effectiveness of interpretable,mathematically founded state estimation models as a reliable and efficient alternative to black-box deep learning systems in safety-critical UAV applications. 展开更多
关键词 Extended Kalman filter UAV tracking multi-object tracking mathematical modeling Bayesian estimation YOLOvl2 topological data analysis persistent homology
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DDoS Attack Tracking Using Multi-Round Iterative Viterbi Algorithm in Satellite Internet 认领 引用 被引量：1
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作者 Guo Wei Xu Jin +2 位作者 Pei Yukui Yin Liuguo Feng Wei 《China Communications》 SCIE EI CSCD 2025年第3期148-163,共16页
Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant ... Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI. 展开更多
关键词 DDoS tracking iterative Viterbi algorithm satellite Internet 6G
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3D numerical manifold method for crack propagation in rock materials using a local tracking algorithm 认领 引用
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作者 Boyi Su Tao Xu +3 位作者 Genhua Shi Michael J.Heap Xianyang Yu Guanglei Zhou 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第6期3449-3463,共15页
The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock mater... The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials. 展开更多
关键词 3D numerical manifold method(3D NMM) Crack propagation Local tracking algorithm Brittle materials
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A tracking algorithm based on adaptive Kalman filter with carrier-to-noise ratio estimation under solar radio bursts interference 认领 引用
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作者 ZHU Xuefen LI Ang +2 位作者 LUO Yimei LIN Mengying TU Gangyi 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第4期880-891,共12页
Solar radio burst(SRB)is one of the main natural interference sources of Global Positioning System(GPS)signals and can reduce the signal-to-noise ratio(SNR),directly affecting the tracking performance of GPS receivers... Solar radio burst(SRB)is one of the main natural interference sources of Global Positioning System(GPS)signals and can reduce the signal-to-noise ratio(SNR),directly affecting the tracking performance of GPS receivers.In this paper,a tracking algorithm based on the adaptive Kalman filter(AKF)with carrier-to-noise ratio estimation is proposed and compared with the conventional second-order phase-locked loop tracking algo-rithms and the improved Sage-Husa adaptive Kalman filter(SHAKF)algorithm.It is discovered that when the SRBs occur,the improved SHAKF and the AKF with carrier-to-noise ratio estimation enable stable tracking to loop signals.The conven-tional second-order phase-locked loop tracking algorithms fail to track the receiver signal.The standard deviation of the carrier phase error of the AKF with carrier-to-noise ratio estimation out-performs 50.51%of the improved SHAKF algorithm,showing less fluctuation and better stability.The proposed algorithm is proven to show more excellent adaptability in the severe envi-ronment caused by the SRB occurrence and has better tracking performance. 展开更多
关键词 solar radio burst(SRB) global positioning system(GPS) adaptive Kalman filter(AKF) tracking algorithm.
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Fishing Ship Trajectory Tracking Control Based on the Closed-Loop Gain Shaping Algorithm Under Rough Sea 认领 引用
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作者 SONG Chun-yu GUO Te-er SUI Jiang-hua 《China Ocean Engineering》 SCIE EI CSCD 2025年第2期365-372,共8页
This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working... This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working environments and safety requirements.The nonlinear feedback method is used to improve the closed-loop gain shaping algorithm.By introducing the sine function,the problem of excessive control energy of the system can be effectively solved.Moreover,an integral separation design is used to solve the influence of the integral term in conventional PID controllers on the transient performance of the system.In this paper,a common 32.98 m large fiberglass reinforced plastic(FRP)trawler is adopted for simulation research at the winds scale of Beaufort No.7.The results show that the track error is smaller than 3.5 m.The method is safe,feasible,concise and effective and has popularization value in the direction of fishing ship trajectory tracking control.This method can be used to improve the level of informatization and intelligence of fishing ships. 展开更多
关键词 trajectory tracking control nonlinear feedback control fishing ship closed-loop gain shaping algorithm rough sea
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Trajectory tracking near asteroids using relaxed Lyapunov-based model predictive control 认领 引用
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作者 YU Zhitong SHANG Haibin +1 位作者 ZHAO Zichen ZHANG Xuefen 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第2期670-686,共17页
Lyapunov-based model predictive control(LMPC)is an effective approach for trajectory tracking because of its wellguaranteed and easy-to-implement stability.However,traditional LMPC utilizes pre-designed auxiliary cont... Lyapunov-based model predictive control(LMPC)is an effective approach for trajectory tracking because of its wellguaranteed and easy-to-implement stability.However,traditional LMPC utilizes pre-designed auxiliary controllers to estimate the domain of attraction(DOA)and construct stability constraints,which inevitably reduces its stable domain and degrades tracking performance.For this problem,this paper proposes a relaxed LMPC(RLMPC)which is designed independently of auxiliary controllers.The control Lyapunov function(CLF)is firstly introduced to decouple the DOA and auxiliary control,alleviating the conservatism in traditional LMPC.Subsequently,a multi-resolution sampling-based search algorithm is developed to estimate the DOA,where the state space is partitioned into hyper-rectangles.A verification condition is derived to extend the verification validity of sampling points to all states within hyper-rectangles,thereby reducing DOA estimation error.Based on the auxiliary-controller-independent DOA(ACI-DOA)and CLF,stability constraints are formulated to ensure stability for RLMPC,while relaxing the stable domain of RLMPC to the entire ACI-DOA.Furthermore,a convergence rate adaptive adjustment technology is developed to enhance the convergence rate while balancing it with control effort.Through numerical simulations involving asteroid orbiting missions,the proposed method is found to significantly expand the stable domain and improve tracking performance. 展开更多
关键词 Lyapunov-based model predictive control(LMPC) trajectory tracking auxiliary-controller-independent domain of attraction(DOA) sampling-based search algorithm control Lyapunov function(CLF) asteroid orbiting mission
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Retina algorithm for heavy-ion tracking in single-event effects localization 认领 引用
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作者 Wen-Di Deng Jin-Chuan Wang +5 位作者 Hui-Peng Pan Wei Zhang Jian-Song Wang Fu-Qiang Wang Zi-Li Li Ren-Zhuo Wan 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2025年第6期123-135,共13页
This study presents a real-time tracking algorithm derived from the retina algorithm,designed for the rapid,real-time tracking of straight-line particle trajectories.These trajectories are detected by pixel detectors ... This study presents a real-time tracking algorithm derived from the retina algorithm,designed for the rapid,real-time tracking of straight-line particle trajectories.These trajectories are detected by pixel detectors to localize single-event effects in two-dimensional space.Initially,we developed a retina algorithm to track the trajectory of a single heavy ion and achieved a positional accuracy of 40μm.This was accomplished by analyzing trajectory samples from the simulations using a pixel sensor with a 72×72 pixel array and an 83μm pixel pitch.Subsequently,we refined this approach to create an iterative retina algorithm for tracking multiple heavy-ion trajectories in single events.This iterative version demonstrated a tracking efficiency of over 97%,with a positional resolution comparable to that of single-track events.Furthermore,it exhibits significant parallelism,requires fewer resources,and is ideally suited for implementation in field-programmable gate arrays on board-level systems,facilitating real-time online trajectory tracking. 展开更多
关键词 Single-event effects Retina algorithm Iterative retina algorithm Heavy ion Particle tracking
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Optimizing high-speed train tracking intervals with an improved multi-objective grey wolf 认领 引用 被引量：2
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作者 Lin Yue Meng Wang +1 位作者 Peng Wang Jinchao Mu 《Railway Sciences》 2025年第3期322-336,共15页
Purpose-With the rapid advancement of China’s high-speed rail network,the density of train operations is on the rise.To address the challenge of shortening train tracking intervals while enhancing transportation effi... Purpose-With the rapid advancement of China’s high-speed rail network,the density of train operations is on the rise.To address the challenge of shortening train tracking intervals while enhancing transportation efficiency,the multi-objective dynamic optimization of the train operation process has emerged as a critical issue.Design/methodology/approach-Train dynamic model is established by analyzing the force of the train in the process of tracing operation.The train tracing operation model is established according to the dynamic mechanical model of the train tracking process,and the dynamic optimization analysis is carried out with comfort,energy saving and punctuality as optimization objectives.To achieve multi-objective dynamic optimization,a novel train tracking operation calculation method is proposed,utilizing the improved grey wolf optimization algorithm(MOGWO).The proposed method is simulated and verified based on the train characteristics and line data of CR400AF electric multiple units.Findings-The simulation results prove that the optimized MOGWO algorithm can be computed quickly during train tracks,the optimum results can be given within 5s and the algorithm can converge effectively in different optimization target directions.The optimized speed profile of the MOGWO algorithm is smoother and more stable and meets the target requirements of energy saving,punctuality and comfort while maximally respecting the speed limit profile.Originality/value-The MOGWO train tracking interval optimization method enhances the tracking process while ensuring a safe tracking interval.This approach enables the trailing train to operate more comfortably,energy-efficiently and punctually,aligning with passenger needs and industry trends.The method offers valuable insights for optimizing the high-speed train tracking process. 展开更多
关键词 Tracking running Train dynamics model Multi-objective optimization MOGWO CR400AF electric multiple units
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An Improved Multi-objective Artificial Hummingbird Algorithm for Capacity Allocation of Supercapacitor Energy Storage Systems in Urban Rail Transit 认领 引用 被引量：1
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作者 Xin Wang Jian Feng Yuxin Qin 《Journal of Bionic Engineering》 SCIE EI CSCD 2025年第2期866-883,共18页
To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved... To address issues such as poor initial population diversity, low stability and local convergence accuracy, and easy local optima in the traditional Multi-Objective Artificial Hummingbird Algorithm (MOAHA), an Improved MOAHA (IMOAHA) was proposed. The improvements involve Tent mapping based on random variables to initialize the population, a logarithmic decrease strategy for inertia weight to balance search capability, and the improved search operators in the territory foraging phase to enhance the ability to escape from local optima and increase convergence accuracy. The effectiveness of IMOAHA was verified through Matlab/Simulink. The results demonstrate that IMOAHA exhibits superior convergence, diversity, uniformity, and coverage of solutions across 6 test functions, outperforming 4 comparative algorithms. A Wilcoxon rank-sum test further confirmed its exceptional performance. To assess IMOAHA’s ability to solve engineering problems, an optimization model for a multi-track, multi-train urban rail traction power supply system with Supercapacitor Energy Storage Systems (SCESSs) was established, and IMOAHA was successfully applied to solving the capacity allocation problem of SCESSs, demonstrating that it is an effective tool for solving complex Multi-Objective Optimization Problems (MOOPs) in engineering domains. 展开更多
关键词 Multi-objective artificial hummingbird algorithm Tent mapping based on random variables Urban rail transit Supercapacitor energy storage systems Capacity allocation
A Review of the Evolution of Multi-Objective Evolutionary Algorithms 认领 引用 被引量：1
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作者 Thomas Hanne Mohammad Jahani Moghaddam 《Computers, Materials & Continua》 SCIE EI 2025年第12期4203-4236,共34页
Multi-Objective Evolutionary Algorithms(MOEAs)have significantly advanced the domain of MultiObjective Optimization(MOO),facilitating solutions for complex problems with multiple conflicting objectives.This review exp... Multi-Objective Evolutionary Algorithms(MOEAs)have significantly advanced the domain of MultiObjective Optimization(MOO),facilitating solutions for complex problems with multiple conflicting objectives.This review explores the historical development of MOEAs,beginning with foundational concepts in multi-objective optimization,basic types of MOEAs,and the evolution of Pareto-based selection and niching methods.Further advancements,including decom-position-based approaches and hybrid algorithms,are discussed.Applications are analyzed in established domains such as engineering and economics,as well as in emerging fields like advanced analytics and machine learning.The significance of MOEAs in addressing real-world problems is emphasized,highlighting their role in facilitating informed decision-making.Finally,the development trajectory of MOEAs is compared with evolutionary processes,offering insights into their progress and future potential. 展开更多
关键词 Multi-objective optimization evolutionary algorithms Pareto-based selection decomposition-based methods advanced analytics
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Dynamic Multi-Objective Gannet Optimization(DMGO):An Adaptive Algorithm for Efficient Data Replication in Cloud Systems 认领 引用
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作者 P.William Ved Prakash Mishra +3 位作者 Osamah Ibrahim Khalaf Arvind Mukundan Yogeesh N Riya Karmakar 《Computers, Materials & Continua》 SCIE EI 2025年第9期5133-5156,共24页
Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple dat... Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance. 展开更多
关键词 Cloud computing data replication dynamic optimization multi-objective optimization gannet optimization algorithm adaptive algorithms resource efficiency scalability latency reduction energy-efficient computing
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An AIoT Monitoring System for Multi-Object Tracking and Alerting 认领 引用 被引量：5
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作者 Wonseok Jung Se-Han Kim +1 位作者 Seng-Phil Hong Jeongwook Seo 《Computers, Materials & Continua》 SCIE EI 2021年第4期337-348,共12页
Pig farmers want to have an effective solution for automatically detecting and tracking multiple pigs and alerting their conditions in order to recognize disease risk factors quickly.In this paper,therefore,we propose... Pig farmers want to have an effective solution for automatically detecting and tracking multiple pigs and alerting their conditions in order to recognize disease risk factors quickly.In this paper,therefore,we propose a novel monitoring system using an Artificial Intelligence of Things(AIoT)technique combining artificial intelligence and Internet of Things(IoT).The proposed system consists of AIoT edge devices and a central monitoring server.First,an AIoT edge device extracts video frame images from a CCTV camera installed in a pig pen by a frame extraction method,detects multiple pigs in the images by a faster region-based convolutional neural network(RCNN)model,and tracks them by an object center-point tracking algorithm(OCTA)based on bounding box regression outputs of the faster RCNN.Finally,it sends multi-pig tracking images to the central monitoring server,which alerts them to pig farmers through a social networking service(SNS)agent in cooperation with an oneM2M-compliant IoT alerting method.Experimental results showed that the multi-pig tracking method achieved the multi-object tracking accuracy performance of about 77%.In addition,we verified alerting operation by confirming the images received in the SNS smartphone application. 展开更多
关键词 Internet of Things multi-object tracking pig pen social network
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Weighted adaptive filtering algorithm for carrier tracking of deep space signal 认领 引用 被引量：9
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作者 Song Qingping Liu Rongke 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2015年第4期1236-1244,共9页
Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is aut... Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is automatic when the signal to noise ratio（SNR） is unknown.If the frequency-locked loop（FLL） or the phase-locked loop（PLL） with fixed loop bandwidth, or Kalman filter with fixed noise variance is adopted, the accretion of estimation error and filter divergence may be caused.Therefore, the Kalman filter algorithm with adaptive capability is adopted to suppress filter divergence.Through analyzing the inadequacies of Sage–Husa adaptive filtering algorithm, this paper introduces a weighted adaptive filtering algorithm for autonomous radio.The introduced algorithm may resolve the defect of Sage–Husa adaptive filtering algorithm that the noise covariance matrix is negative definite in filtering process.In addition, the upper diagonal（UD） factorization and innovation adaptive control are used to reduce model estimation errors,suppress filter divergence and improve filtering accuracy.The simulation results indicate that compared with the Sage–Husa adaptive filtering algorithm, this algorithm has better capability to adapt to the loop, convergence performance and tracking accuracy, which contributes to the effective and accurate carrier tracking in low SNR environment, showing a better application prospect. 展开更多
关键词 Adaptive algorithms Carrier tracking Deep space communicationKalman filters Tracking accuracy Weighted
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A decoupled multi-objective optimization algorithm for cut order planning of multi-color garment 认领 引用
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作者 DONG Hui LYU Jinyang +3 位作者 LIN Wenjie WU Xiang WU Mincheng HUANG Guangpu 《High Technology Letters》 EI CAS 2025年第1期53-62,共10页
This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is establish... This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises. 展开更多
关键词 multi-objective optimization non-dominated sorting in genetic algorithmsⅡ(NSGAII) cut order planning(COP) multi-color garment linear programming decoupling strategy
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Research on Trajectory Tracking Method of Redundant Manipulator Based on PSO Algorithm Optimization 认领 引用 被引量：3
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作者 Shifu Xu Yanan Jiang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第10期401-415,共15页
Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize,the trajectory tracking method of redundant manipulator based on PS... Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize,the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied.The kinematic diagram of redundant manipulator is created,to derive the equation of motion trajectory of redundant manipulator end.Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy.Based on the tracking ellipse of redundant manipulator,the tracking shape of redundant manipulator is determined with the overall tracking index as the second index,and the optimization method of tracking index is proposed.The redundant manipulator contour is located by active contour model,on this basis,combined with particle swarm optimization algorithm,the point coordinates on the circumference with the relevant joint point as the center and joint length as the radius are selected as the algorithm particles for iteration,and the optimal tracking results of the overall redundant manipulator trajectory are obtained.The experimental results show that under the proposed method,the tracking error of the redundant manipulator is low,and the error jump range is small.It shows that this method has high tracking accuracy and reliability. 展开更多
关键词 PSO algorithm optimization redundant manipulator trajectory tracking overall tracking index
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A novel estimation algorithm for torpedo tracking in undersea environment 认领 引用 被引量：2
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作者 D.V.A.N.RAVI KUMAR S.KOTESWARA RAO K.PADMA RAJU 《Journal of Central South University》 SCIE EI CAS CSCD 2019年第3期673-683,共11页
A novel estimation algorithm is introduced to handle the popular undersea problem called torpedo tracking with angle-only measurements with a better approach compared to the existing filters. The new algorithm produce... A novel estimation algorithm is introduced to handle the popular undersea problem called torpedo tracking with angle-only measurements with a better approach compared to the existing filters. The new algorithm produces a better estimate from the outputs produced by the traditional nonlinear approaches with the assistance of simple noise minimizers like maximum likelihood filter or any other algorithm which belongs to their family. The introduced method is extended to the higher version in two ways. The first approach extracts a better estimate and covariance by enhancing the count of the intermediate filters, while the second approach accepts more inputs so as to attain improved performance without enhancement of the intermediate filter count. The ideal choice of the placement of towed array sensors to improve the performance of the proposed method further is suggested as the one where the line of sight and the towed array are perpendicular. The results could get even better by moving the ownship in the direction of reducing range. All the results are verified in the MATLAB environment. 展开更多
关键词 estimation algorithm torpedo tracking angle-only measurements line of sight maximum likelihood filter
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Multi-object tracking based on behaviour and partial observation 认领 引用 被引量：1
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作者 路红 费树岷 +1 位作者 郑建勇 张涛 《Journal of Southeast University(English Edition)》 EI CAS 2008年第4期468-472,共5页
To cope with multi-object tracking under real-world complex situations, a new video-based method is proposed. In the detecting step, the moving objects are segmented with the third level DWT （discrete wavelet transfo... To cope with multi-object tracking under real-world complex situations, a new video-based method is proposed. In the detecting step, the moving objects are segmented with the third level DWT （discrete wavelet transform ）and background difference. In the tracking step, the Kalman filter and scale parameter are used first to estimate the object position and bounding box. Then, the center-association-based projection ratio and region-association-based occlusion ratio are defined and combined to judge object behaviours. Finally, the tracking scheme and Kalman parameters are adaptively adjusted according to object behaviour. Under occlusion, partial observability is utilized to obtain the object measurements and optimum box dimensions. This method is robust in tracking mobile objects under such situations as occlusion, new appearing and stablization, etc. Experimental results show that the proposed method is efficient. 展开更多
关键词 multi-object tracking projection ratio occlusion ratio behaviour partial observation Kalman filter
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