检索结果-内蒙古大学图书馆

Wireless multimedia sensor network video object detection method using dynamic clustering algorithm

MULTIMEDIA TOOLS AND APPLICATIONS 2020年第23-24期79卷 16927-16940页

作者： Shao, Yilin Shangqiu Polytech Sch Comp Shangqiu 476100 Henan Peoples R China

Most of the traditional tracking algorithms use the Kalman filter to predict the tracking process. Although the tracking accuracy is relatively high, the calculation is large and the time complexity is high. Based on this research, this paper proposes a dynamic clustering target tracking algorithm for motion trends. The algorithm forms a dynamic cluster in the network, and the cluster head dynamically schedules the nodes to achieve collaborative tracking of the targets. The tracking strategy is mainly divided into two stages: First, the cluster head establishes a "neighbor node set" within its communication range, and selects the neighbor node in the "neighbor node set" according to the distance between the node and the target to construct the "intra-cluster member set" to perform the target on the target. Tracking;as the target moves continuously, the cluster head updates the members in the cluster at regular intervals, removes the nodes that have lost the target monitoring from the cluster, and adds the new nodes to the cluster;secondly, elects a new cluster head;if current When the cluster head is no longer suitable to continue to serve as the cluster head, the current cluster head selects the node in the "intra-cluster member set" as the new cluster head of the next work cycle;according to the moving direction of the target, selects the node with the best moving tendency of the target For the new cluster head, this allows the new cluster head to have a longer duty cycle and avoid frequent replacement of the cluster head;the new cluster head continues to set up the dynamic cluster to track the target until the target moves out of the monitoring area. The simulation results show that the proposed algorithm is more efficient than the traditional target tracking method.

关键词： Target detection Wireless multimedia Sensor network video dynamic clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

An Improved dynamic clustering algorithm Based on Uplink Capacity Analysis in Ultra-Dense Network System 9th

An Improved Dynamic Clustering Algorithm Based on Uplink Cap...

引用

9th European-Alliance-for-Innovation (EAI) International Wireless Internet Conference (WICON)

作者： Zeng, Jie Zhang, Qi Su, Xin Rong, Liping Tsinghua Univ Tsinghua Natl Lab Informat Sci & Technol Res Inst Informat Technol Beijing Peoples R China

ISBN: (纸本)9783319729985;9783319729978

The Ultra-Dense Network (UDN) system is considered as a promising technology in the future wireless communication. Different from the existing heterogeneous network, UDN has a smaller cell radius and a new network structure. The core concept of UDN is to deploy the Low Power Base Stations (LPBSs). With denser cells, the interference scenario is even severer in UDN than Long Term Evolution (LTE) heterogeneous network. clustering cooperation should reduce interference among the cells. In this paper, we firstly derive the total uplink capacity of the whole system. Then we present a novel dynamic clustering algorithm. The objective of this algorithm for densely deployed small cell network is to make a better tradeoff between the system performance and complexity, while overcome the inter-Mobile Station (MS) interference. Simulation results show that our approach yields significant capacity gains when compared with some proposed clustering algorithms.

关键词： Ultra-Dense Network Uplink capacity dynamic clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

A dynamic Cell clustering algorithm for Maximization of Coordination Gain in Uplink Coordinated System

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2016年第3期65卷 1752-1760页

作者： Yoon, Misun Kim, Myoung-Seok Lee, Chungyong Yonsei Univ Sch Elect & Elect Engn Seoul 120749 South Korea Samsung Elect Network Business Suwon 443742 South Korea

We propose a dynamic clustering algorithm for maximizing a coordination gain in the uplink coordinated system. The dynamic clustering algorithm configures clusters periodically to adopt the change of the channel environment. Since the greedy-search clustering algorithm does not guarantee cell-edge users' performance and the full-search clustering algorithm (FSCA) is highly complex, we define a coordination gain between the coordinated communication system and the single-cell communication system, as a new parameter, to maximize the benefit of the coordinated communication system. We develop a maximum coordination gain (MAX-CG) clustering algorithm to maximize the coordination gain and an interference weight (IW) clustering algorithm to reduce complexity and guarantee the data rate of cell-edge users. Simulation results show that the MAX-CG clustering algorithm improves the average user rate and the 5% edge user rate. The IW clustering algorithm improves the 5% edge user's rate, guarantees the fairness among the cells, and reduces the complexity to only half of the existing algorithm.

关键词： Coordinated system coordination gain dynamic clustering algorithm interference weight (IW)

来源：评论

学校读者我要写书评

暂无评论

A framework for initialising a dynamic clustering algorithm: ART2-A 5

A framework for initialising a dynamic clustering algorithm:...

引用

IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： Chambers, Simon J. Jarman, Ian H. Lisboa, Paulo J. G. Liverpool John Moores Univ Sch Comp & Math Sci Liverpool L3 3AF Merseyside England

ISBN: (纸本)9781479945184

algorithms in the Adaptive Resonance Theory (ART) family adapt to structural changes in data as new information presents, making it an exciting candidate for dynamic online clustering of big health data. Its use however has largely been restricted to the signal processing field. In this paper we introduce an refinement of the ART2-A method within an adapted separation and concordance (SeCo) framework which has been shown to identify stable and reproducible solutions from repeated initialisations that also provides evidence for an appropriate number of initial clusters that best calibrates the algorithm with the data presented. The results show stable, reproducible solutions for a mix of real-world heath related datasets and well known benchmark datasets, selecting solutions which better represent the underlying structure of the data than using a single measure of separation. The scalability of the method and it's facility for dynamic online clustering makes it suitable for finding structure in big data.

关键词： Big Data adaptive resonance theory medical information systems pattern clustering ART2-A SeCo adapted separation and concordance framework adaptive resonance theory family benchmark datasets big health data dynamic clustering algorithm dynamic online clustering real-world heath related datasets signal processing field Big data Breast cancer clustering algorithms Heuristic algorithms Prototypes Subspace constraints Vectors big data clustering algorithms adaptive resonance theory medical information systems Heuristic algorithms Cluster Analysis Subspace constraints signal processing PROTOTYPE Breast Cancer

来源：评论

学校读者我要写书评

暂无评论

MCDM-FIS-Based Charging Scheduling for Wireless Rechargeable Sensor Networks

引用

IEEE SENSORS JOURNAL 2025年第9期25卷 16182-16197页

作者： Aziz, Samah Abdel Wang, Xingfu Hawbani, Ammar Miao, Fuyou Alsheavi, Amar N. Saeed, Nasir Abdalla, Alwaseela Ismail, A. S. Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026 Peoples R China Zagazig Univ Dept Math & Comp Sci Zagazig 44519 Egypt Shenyang Aerosp Univ Sch Comp Sci Shenyang 110136 Peoples R China Sanaa Univ Dept Math & Comp Sci Sanaa Yemen United Arab Emirates Univ Dept Elect & Commun Engn Al Ain Yemen Colorado State Univ Dept Agr Biol Ft Collins CO 80523 USA Shenzhen Univ Coll Life Sci & Oceanog Shenzhen 518060 Peoples R China

The integration of wireless power transfer (WPT) provides a promising solution to address energy limitations in IoT, 5G, and 6G applications. Despite extensive efforts, distributing multiple wireless charging vehicles (WCVs) and scheduling their charging for efficient energy replenishment in wireless rechargeable sensor networks (WRSNs) remains a considerable challenge, leaving a gap in achieving optimal solutions. This article addresses these challenges by formulating the charging scheduling problem in WRSNs, which utilizes multiple WCVs as a multicriteria decision-making (MCDM) problem. We propose a solution that involves two primary steps: 1) a dynamic clustering algorithm is used to partition the deployment area into subareas. After network initialization, the base station (BS) collects sensor nodes in a charging queue. Then, a computation occurs to calculate the total energy required for all sensor nodes in the queue. After the computation, the BS determines the number of clusters based on the available WCVs;and 2) each cluster utilizes an MCDM approach through a fuzzy inference system (FIS) to prioritize nodes for recharging based on multiple network attributes, including remaining energy (RE), distance to the WCV, consumption rate (CR), node density (ND), and time request (TR). The FIS helps identify the sensor node that most requires charging. Our simulation shows that our method outperforms the state-of-the-art techniques in increasing the survival rate (SR), reducing the number of dead nodes, and enhancing the energy utilization efficiency.

关键词： Charging scheduling dynamic clustering algorithm fuzzy inference system (FIS) wireless rechargeable sensor networks (WRSNs) Charging scheduling dynamic clustering algorithm fuzzy inference system (FIS) wireless rechargeable sensor networks (WRSNs)

来源：评论

学校读者我要写书评

暂无评论

dynamic clustering of Multipath Components for Time-Varying Propagation Channels

引用

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2021年第12期70卷 13396-13400页

作者： Sun, Guiqi He, Ruisi Ai, Bo Huang, Chen Zhong, Zhangdui Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Zhengzhou Univ Sch Informat Engn Zhengzhou 450001 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China Purple Mt Labs Nanjing 210000 Peoples R China

dynamic channel clustering and modeling have recently attracted much interest. Extensive channel measurements have shown that multipath components (MPCs) generally exist as clusters. Therefore, an accurate clustering algorithm is required to model the time-varying channels. However, the dynamic behaviors of MPCs have not been well considered in the existing algorithms. In this paper, we present a new metric for MPCs' clustering in time-variant channels, which considers MPC's evolution in time domain and clusters MPCs based on the fluctuation and multi-dimension distance of MPC's trajectories. The performance of the new metric is verified by comparing measurements and simulations. It is found that the proposed algorithm using the new metric can well recognize the dynamic behaviors of MPCs and identify time-varying clusters accurately.

关键词： Trajectory Heuristic algorithms clustering algorithms Vehicle dynamics Kalman filters Time-varying channels Time measurement Multipath components dynamic clustering algorithm tracking trajectory fluctuation directional derivative

来源：评论

学校读者我要写书评

暂无评论

Evaluating accession decisions in customs unions: a dynamic machine learning approach

引用

INTERNATIONAL ECONOMICS AND ECONOMIC POLICY 2025年第1期22卷 1-27页

作者： Naeher, Dominik De Lombaerde, Philippe Saber, Takfarinas Univ Goettingen Dept Dev Econ Waldweg 26 D-37073 Gottingen Germany Neoma Business Sch Rouen France United Nations Univ Inst Comparat Reg Integrat Stu Brugge Belgium Vrije Univ Brussel Brussels Belgium Natl Univ Ireland Lero the Irish Software Res Ctr Sch Comp Sci Dublin Ireland

Previous work in the literature on regional economic integration has proposed the use of machine learning algorithms to evaluate the composition of customs unions, specifically, to estimate the degree to which customs unions match "natural markets" arising from trade flow data or appear to be driven by other factors such as political considerations. This paper expands upon the static approaches used in previous studies to develop a dynamic framework that allows to evaluate not only the composition of customs unions at a given point in time, but also changes in the composition over time resulting from accessions of new member states. We then apply the dynamic algorithm to evaluate the evolution of the global landscape of customs unions using data on bilateral trade flows of 200 countries from 1958 to 2018. A key finding is that there is considerable variation across different accession rounds of the European Union as to the extent to which these are aligned with the structure of "natural markets," with some accession rounds following more strongly a commercial logic than others. Similar results are also found for other customs unions in the world, complementing the insights obtained from static analyses.

关键词： Regional integration Customs union Accession Machine learning dynamic clustering algorithm C60 F13 F15 F60

来源：评论

学校读者我要写书评

暂无评论

Snow depth estimation based on GNSS-IR cluster analysis

引用

MEASUREMENT SCIENCE AND TECHNOLOGY 2021年第9期32卷 095801-095801页

作者： Zhang, Shuangcheng Zhang, Chenglong Zhao, Ying Li, Hao Liu, Qi Pang, Xiaoguang Changan Univ Coll Geol Engn & Geomant Xian Shaanxi Peoples R China China Meteorol Adm Urumqi Inst Desert Meteorol Urumqi Xinjiang Peoples R China

As the most influential factor of the cryosphere, snow is the weathervane of climate change. Real-time and accurate snow monitoring data play an important role in climate-change indication, water resource management, disaster prevention, and mitigation. As traditional snow monitoring cannot meet the current requirements, since 2007, the signal-to-noise ratio data has been used for snow-depth inversion. The accuracy of the long time-series global navigation satellite system interferometric reflectometry (GNSS-IR) is not high, although it is significantly better compared to the previous methods. When the ground is covered by shallow snow or there is no snow, the snow-depth inversion is affected by the vegetation and snow layer, lowering the reliability of the Lomb-Scargle spectrum (LSP) analysis, and reducing the snow-depth inversion accuracy. To address the instability of the LSP results, in this study, the dynamic clustering algorithm is used for screening the PSD of the LSP results, and the influence of the signal penetration is eliminated. The average peak of the frequency based on multi-satellite LSP is obtained, and finally, the Grubbs criterion is utilized for improving the reliability of the results. The data of the Altay GNSS snow monitoring station at Altay in Xinjiang and the plate boundary observation SG27 and P351 sites are used as the research data, and a representative time period for the snow depth is selected. The inversion snow depth of the traditional GNSS-IR method are compared with those of the improved GNSS-IR. The experimental results demonstrate that improved GNSS-IR results had better match with the measured snow depth.

关键词： ground-based GNSS-IR Altay signal-to-noise ratio dynamic clustering algorithm Grubbs criterion

来源：评论

学校读者我要写书评

暂无评论

Cluster-based mobility management algorithms for wireless mesh networks

引用

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2018年第11期31卷 e3595-e3595页

作者： Rao, Y. Mallikarjuna Subramanyam, M. V. Prasad, K. Satya Jawaharlal Nehru Technol Univ Kakinada Kakinada Andhra Pradesh India Santhiram Engn Coll Nandyal Andhra Pradesh India KL Univ Guntur Andhra Pradesh India

Wireless mesh networks (WMNs) have been the recent advancements and attracting more academicians and industrialists for their seamless connectivity to the internet. Radio resource is one among the prime resources in wireless networks, which is expected to use in an efficient way especially when the mobile nodes are on move. However, providing guaranteed quality of service to the mobile nodes in the network is a challenging issue. To accomplish this, we propose 2 clustering algorithms, namely, static clustering algorithm for WMNs and dynamic clustering algorithm for WMNs. In these algorithms, we propose a new weight-based cluster head and cluster member selection process for the formation of clusters. The weight of the nodes in WMN is computed considering the parameters include the bandwidth of the node, the degree of node connectivity, and node cooperation factor. Further, we also propose enhanced quality of service enabled routing protocol for WMNs considering the delay, bandwidth, hopcount, and expected transmission count are the routing metrics. The performance of the proposed clustering algorithms and routing protocol are analyzed, and results show high throughput, high packet delivery ratio, and low communication cost compared with the existing baseline mobility management algorithms and routing protocols.

关键词： clustering dynamic clustering algorithm mobility management quality of service static clustering algorithm wireless mesh networks

来源：评论

学校读者我要写书评

暂无评论

The creation of a representative driving cycle based on Intelligent Transportation System (ITS) and a mathematically statistical algorithm: A case study of Changchun (China)

引用

SUSTAINABLE CITIES AND SOCIETY 2018年 42卷 301-313页

作者： Zhao, Jingyuan Gao, Yinhan Guo, Jianhua Chu, Liang Jilin Univ State Key Lab Automot Simulat & Control Changchun 130022 Jilin Peoples R China Univ Calif Davis Inst Transportat Studies Davis CA 95616 USA

This paper is concerned with the development of a representative driving cycle that has advantages in accuracy and robustness. There are two aspects to achieve the representativeness of the developed driving cycle. Foremost, the on-road driving patterns derive from a sufficient and objective database. Secondly, the simplicity and accuracy of the construction methodology are taken into full deliberation. To achieve these, the first issue is solved by making a combination of the official statistical data and Intelligent Transportation System, instead of determining the test routes via subjectivity and experience. Specifically, the official statistical data support the road classification and characteristic. In parallel, it is instrumental to take advantage of traffic information network provided by Google Waze intelligent application. The second issue is accomplished with dynamic clustering algorithm, which is tremendously appealing in practice. In the proposed method, the comprehensive principal component score (CPCS) is created to cluster the micro-trips into more homogeneous groups of observations. The Euclidean distance and iterative rapidity of convergence illustrate that CPCS-based dynamic clustering outperforms poly-principal components-based with respect to clustering performance and complexity. The robustness assessments verify the developed driving cycle matches the real-world driving cycle characteristics with high resolution under well-designed experiments and simulations.

关键词： Representative driving cycle Intelligent Transportation System Comprehensive principal component scores ANOVA dynamic clustering algorithm Robustness assessments

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：