检索结果-南通市图书馆

Design of Congestion Control Strategy Based on Pipeline Flux Leak Monitoring Networks

在线全文

学校读者我要写书评

暂无评论

Journal of Donghua University(English Edition) 2009年第5期26卷 554-558页

作者：周鹏 College of Information Engineering Tarim University

Flow against pipeline leakage and the pipe network sudden burst pipe to pipeline leakage flow for the application objects,network congestion avoidance strategy is designed in pipeline leak *** on the property of Markov chain for network data,a new estimator with particle filter is proposed for congestion control in this *** proposed scheme can predict the traffic patterns by the decision-making *** compare with previous scheme based on fuzzy neural network,the proposed scheme can adaptively adjust the network rate in real-time and reduce the cell loss rate,so that it can avoid the traffic *** results show that network congestion avoidance strategy with particle filter can improve the bandwidth utilization,Transmission Control Protocol (TCP) friendliness and reduce the packet drop rate in Pipeline Flux Leak Monitoring networks.

关键词： transmission control protocol congestioncontrol particle filter cell loss rate QoS networks

On the sensitive areas for targeted observations in ENSO forecasting

在线全文

学校读者我要写书评

暂无评论

Atmospheric and Oceanic Science Letters 2021年第5期14卷 19-23页

作者： Jingjing Zhang Shujuan Hu Wansuo Duan College of Atmospheric Sciences Lanzhou UniversityLanzhouChina State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences BeijingChina

Using the outputs from CMCC-CM in CMIP5 experiments,the authors identified sensitive areas for targeted observations in ENSO forecasting from the perspective of the initial error growth(IEG)method and the particle filter(PF)*** showed that the PF targets areas over the central-eastern equatorial Pacific,while the sensitive areas determined by the IEG method are slightly to the east of the *** a small part of the areas targeted by the IEG method also lie in the southeast equatorial Pacific,this does not affect the large-scale overlapping of the sensitive areas determined by these two methods in the eastern equatorial ***,sensitive areas determined by the two methods are mutually *** considering the uncertainty of methods for determining sensitive areas in realistic targeted observation,it is more reasonable to choose the above overlapping areas as sensitive areas for ENSO *** result provides scientific guidance for how to better determine sensitive areas for ENSO forecasting.

关键词： Targeted observation ENSO particle filter Initial error

Shape-constrained semiparametric additive stochastic volatility models

在线全文

学校读者我要写书评

暂无评论

Statistical Theory and Related Fields 2019年第1期3卷 71-82页

作者： Jiangyong Yin Peter F.Craigmile Xinyi Xu Steven MacEachern Department of Statistics The Ohio State UniversityColumbusOHUSA

Nonparametric stochastic volatility models,although providing great flexibility for modelling thevolatility equation,often fail to account for useful shape *** example,a model maynot use the knowledge that the autoregressive component of the volatility equation is monotonically increasing as the lagged volatility *** propose a class of additive stochasticvolatility models that allow for different shape constraints and can incorporate the leverageeffect–asymmetric impact of positive and negative return shocks on *** developa Bayesian fitting algorithm and demonstrate model performance on simulated and *** general nonparametric models,our model sacrifices little when the true volatility equation is *** nonlinear situations we improve the model fit and the ability to estimatevolatilities over general,unconstrained,nonparametric models.

关键词： Bayesian isotonic regression leverage effect Markov chain Monte Carlo nonlinear time series particle filter state space model

A NOVEL FAST MOVING OBJECT CONTOUR TRACKING ALGORITHM

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Electronics(China) 2009年第1期26卷 94-100页

作者： An Guocheng Yang Hao Wu Zhenyang School of Information Science and Engineering Southeast University Nanjing 210096 China

If a somewhat fast moving object exists in a complicated tracking environment, snake's nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if the object goes beyond the limits of mean shift snake module operation in suc- cessive sequences, mean shift snake's nodes may also fall into the local minima in their moving to the new object position. This paper presents a motion compensation strategy by using particle filter; therefore a new particle filter Mean Shift Snake (PFMSS) algorithm is proposed which combines particle filter with mean shift snake to fulfill the estimation of the fast moving object contour. Firstly, the fast moving object is tracked by particle filter to create a coarse position which is used to initialize the mean shift algorithm. Secondly, the whole relevant motion information is used to compensate the snake's node positions. Finally, snake algorithm is used to extract the exact object contour and the useful information of the object is fed back. Some real world sequences are tested and the results show that the novel tracking method have a good performance with high accuracy in solving the fast moving problems in cluttered background.

关键词： Object contour tracking Mean shift particle filter Kernel scale

EFFECTIVE APPEARANCE MODEL FOR PROBABILISTIC OBJECT TRACKING

在线全文

学校读者我要写书评

暂无评论

Journal of Electronics(China) 2009年第4期26卷 503-508页

作者： Wang Shupeng Ji Hongbing School of Electronic Engineering Xidian University Xi＇an 710071 China School of Communication and Information Engineering Xi＇an University of Science and Technology Xi＇an 7100541 China

This paper presents a robust object tracking approach via a spatially constrained colour model. Local image patches of the object and spatial relation between these patches are informative and stable during object tracking. So, we propose to partition an object into patches and develop a Spatially Constrained Colour Model (SCCM) by combining the colour distributions and spatial configuration of these patches. The likelihood of the candidate object is given by estimating the confidences of the pixels in the candidate object region. The appearance model is learnt from the first frame and the tracking is carried out by particle filter. The experimental results show that the proposed tracking approach can accurately track the object with scale changes, pose variance and partial occlusion.

关键词： Object tracking Appearance model particle filter Adaptive scale

Relative discriminant coefficient based multi-cue fusion for robust object tracking

在线全文

学校读者我要写书评

暂无评论

Frontiers of Electrical and Electronic Engineering in China 2008年第3期3卷 274-282页

作者： Jiangtao WANG Jingyu YANG Department of Computer Science Nanjing University of Science and TechnologyNanjing 210094China

In visual tracking,integrating multiple cues will increase the reliability and robustness of the tracking system in situations where no single cue is *** this paper,a novel multi-cue based tracking method is presented under the particle filter *** both practical distance and Bhattacharyya distance between particles and the target,a parameter called relative discriminant coefficient(RDC)is designed to measure the tracking ability for different ***-cue fusion is carried out in a reweighing manner based on this *** results demonstrate the high robustness and effectiveness of our method in handling appearance changes,cluttered background,illumination changes and occlusions.

关键词： visual tracking multi-cue fusion particle filter

An Improved FastSLAM Method Based on Niche Technique and particle Swarm Optimization

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Improved FastSLAM Method Based on Niche Technique and Par...

Underground Coal Mine Target Tracking via Multi-Feature Joint Sparse Representation

2011 Chinese Control and Decision Conference（CCDC）

作者： Zou Zhirong,Cai Zixing,and Chen Baifan

FastSLAM is a well-known solution based on particle filter to the simultaneous localization and mapping （SLAM） problem for mobile *** performance of the conventional FastSLAM degrades over time due to the particle depletion and it needs a large number of particles to be maintained at a high *** paper presents an improved FastSLAM method in which niche technique and particle swarm optimization are integrated into the conventional *** means of the multi-modal optimization,the diversity and search ability of particles are both enhanced,and the estimation performance of particle filter is improved,so that particles would be concentrated around the true state of the mobile robot,and the precision of SLAM would be *** experiment results show that the improved method is effective in SLAM,and its performance is robust even in the case of only a few particles.

关键词： Simultaneous localization and mapping particle filter particle swarm optimization Niche technique

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Journal of Computer and Communications 2021年第3期9卷 118-132页

作者： Yan Lu Qingxiang Huang College of Energy Science and Engineering Xi’an University of Science and Technology Xi’an China

Single-feature methods are unable to effectively track a target in an underground coal mine video due to the high background noise, low and uneven illumination, and drastic light fluctuation in the video. In this study, we propose an underground coal mine personnel target tracking method using multi-feature joint sparse representation. First, with a particle filter framework, the global and local multiple features of the target template and candidate particles are extracted. Second, each of the candidate particles is sparsely represented by a dictionary template, and reconstruction is achieved after solving the sparse coefficient. Last, the particle with the lowest reconstruction error is deemed the tracking result. To validate the effectiveness of the proposed algorithm, we compare the proposed method with three commonly employed tracking algorithms. The results show that the proposed method is able to reliably track the target in various scenarios, such as occlusion and illumination change, which generates better tracking results and validates the feasibility and effectiveness of the proposed method.

关键词： Underground Coal Mine Sparse Representation particle filter Multi-Feature Target-Tracking

VIDEO MULTI-TARGET TRACKING BASED ON PROBABILISTIC GRAPHICAL MODEL

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Electronics(China) 2011年第4期28卷 548-557页

作者： Xu Feng Huang Chenrong Wu Zhengjun Xu Lizhong College of Computer and Information Engineering Hohai University Nanjing 210098 China School of Computer Engineering Nanjing Institute of Technology Nanjing 211167 China

In the technique of video multi-target tracking,the common particle filter can not deal well with uncertain relations among multiple *** solve this problem,many researchers use data association method to reduce the multi-target ***,the traditional data association method is difficult to track accurately when the target is *** remove the occlusion in the video,combined with the theory of data association,this paper adopts the probabilistic graphical model for multi-target modeling and analysis of the targets relationship in the particle filter ***-perimental results show that the proposed algorithm can solve the occlusion problem better compared with the traditional algorithm.

关键词： Video tracking Multi-target tracking Data association Probabilistic graphical model particle filter