检索结果-南通市图书馆

Wind and Photovoltaic Power Time Series Data Aggregation Method Based on an Ensemble Clustering and Markov chain

CSEE Journal of Power and Energy Systems 2022年第3期8卷 757-768页

作者： Jingxin Jin Lin Ye Jiachen Li Yongning Zhao Peng Lu Weisheng Wang Xuebin Wang College of Information and Electrical Engineering China Agricultural UniversityBeijing100083China School of Engineering Cardiff UniversityCF243AAUK China Electric Power Research Institute Beijing100192China State Grid Qinghai Electric Power Company Xining810000China

Reducing the input wind and photovoltaic power time series data can improve the efficiency of time sequential simulations.In this paper,a wind and photovoltaic power time series data aggregation method based on an ensemble clustering and Markov chain(ECMC)is proposed.The ECMC method can effectively reduce redundant information in the data.First,the wind and photovoltaic power time series data were divided into scenarios,and ensemble clustering was used to cluster the divided scenarios.At the same time,the Davies-Bouldin Index(DBI)is adopted to select the optimal number of clusters.Then,according to the temporal correlation between wind and photovoltaic scenarios,the wind and photovoltaic clustering results are merged and reduced to form a set of combined typical day scenarios that can reflect the characteristics of historical data within the calculation period.Finally,based on the Markov chain,the state transition probability matrix of various combined typical day scenarios is constructed,and the aggregation state sequence of random length is generated,and then,the combined typical day scenarios of wind and photovoltaic were sampled in a sequential one-way sequence according to the state sequence and then are built into a representative wind and photovoltaic power time series aggregation sequence.A provincial power grid was chosen as an example to compare the multiple evaluation indexes of different aggregation methods.The results show that the ECMC aggregation method improves the accuracy and efficiency of time sequential simulations.

关键词： Aggregation method ensemble clustering Markov chain time sequential simulations wind and photovoltaic power time series data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Distance Matrix and Markov chain Based Sensor Localization in WSN

引用

Computers, Materials & Continua 2022年第5期71卷 4051-4068页

作者： Omaima Bamasaq Daniyal Alghazzawi Surbhi Bhatia Pankaj Dadheech Farrukh Arslan Sudhakar Sengan Syed Hamid Hassan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia Department of Computer Science and Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthanIndia University of Engineering and Technology LahorePakistan Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveliTamilnaduIndia

Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of interest.Relevant geometries of the surrounding environment are essential to establish a successful WSN topology.But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes(SN)in a WSN is always a challenging task.In this research paper,Distance Matrix and Markov chain(DM-MC)model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node.The method further employs a Markov chain Model(MCM)for energy optimization and interference reduction.Experiments are performed against two well-known models,and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing models.Transition probability is used in the markova chain to sustain higher energy nodes.Finally,the proposed Distance Matrix and Markov chain model decrease energy use by 31%and 25%,respectively,compared to the existing DV-Hop and CSA methods.The experimental results were performed against two proven models,Distance VectorHop Algorithm(DV-HopA)and Crow Search Algorithm(CSA),showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption(EC).These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.

关键词： Wireless sensor network resource optimization routing distance matrix Markov chain

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Chan–Vese Model Based on the Markov chain for Unsupervised Medical Image Segmentation

引用

Tsinghua Science and Technology 2021年第6期26卷 833-844页

作者： Quanwei Huang Yuezhi Zhou Linmi Tao Weikang Yu Yaoxue Zhang Li Huo Zuoxiang He Key Laboratory of Pervasive Computing(Ministry of Education)and the Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China School of Electronic and Information Engineering Beihang UniversityBeijing 100191China Department of Nuclear Medicine Peking Union Medical College HospitalBeijing 100730China School of Clinical Medicine Tsinghua Universityand also with Beijing Tsinghua Changgung HospitalBeijing 100084China

The accurate segmentation of medical images is crucial to medical care and research;however, many efficient supervised image segmentation methods require sufficient pixel level labels. Such requirement is difficult to meet in practice and even impossible in some cases, e.g., rare Pathoma images. Inspired by traditional unsupervised methods, we propose a novel Chan–Vese model based on the Markov chain for unsupervised medical image segmentation. It combines local information brought by superpixels with the global difference between the target tissue and the background. Based on the Chan–Vese model, we utilize weight maps generated by the Markov chain to model and solve the segmentation problem iteratively using the min-cut algorithm at the superpixel level.Our method exploits abundant boundary and local region information in segmentation and thus can handle images with intensity inhomogeneity and object sparsity. In our method, users gain the power of fine-tuning parameters to achieve satisfactory results for each segmentation. By contrast, the result from deep learning based methods is rigid.The performance of our method is assessed by using four Computerized Tomography(CT) datasets. Experimental results show that the proposed method outperforms traditional unsupervised segmentation techniques.

关键词： medical image unsupervised segmentation Markov chain

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

UWB positioning enhancement using Markov chain in indoor NLOS environment

引用

The Journal of China Universities of Posts and Telecommunications 2020年第4期27卷 54-58,98页

作者： Li Shaoxian Lii Fan Wang Chengrui Hou Yanzhao International School Beijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

The accuracy of the positioning system in indoor environment is often affected by none-line-of-sight(NLOS) propagation. In order to improve the positioning accuracy in indoor NLOS environment, a method used ultra-wide-band(UWB) technology, which based on time of arrival(TOA) principle, combining Markov chain and fingerprint matching was proposed. First, the TOA algorithm is used to locate the target tag. Then the Markov chain is used to identify if blocking happened and revise the position result. And the fingerprint matching is used to further improve the position accuracy. Finally, an experiment system was built to test the accuracy of the proposed method and the traditional Kalman filter method. The experimental results show that, compared with the traditional Kalman filter method, the proposed method can improve the positioning accuracy in indoor NLOS environment.

关键词： wireless location time of arrival(TOA) ultra-wide band(UWB) Markov chain fingerprint matching

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

An Algorithm Based on Markov chain to Improve Edge Cache Hit Ratio for Blockchain-Enabled IoT

引用

China Communications 2020年第9期17卷 66-76页

作者： Hongman Wang Yingxue Li Xiaoqi Zhao Fangchun Yang Institute of Network Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Engineering Research Center of Information Network Ministry of EducationBeijing 100876China

Reasonable allocation of storage and computing resources is the basis of building big data system.With the development of IoT(Internet of Things),more data will be brought.A three-layer architecture includes smart devices layer,edge cloud layer and blockchain-based distributed cloud layer.Blockchain is used in IoT for building a distributed decentralize P2P architecture to deal with the secure issue while edge computing deals with increasing volume of data.Edge caching is one of the important application scenarios.In order to allocate edge cache resources reasonably,to improve the quality of service and to reduce the waste of bandwidth resources,this paper proposes a content selection algorithm of edge cache nodes.The algorithm adopts Markov chain model,improves the utilization of cache space and reduces the content transmission delay.The hierarchical caching strategy is adopted and the secondary cache stores slides of contents to expand the coverage of cached content and to reduce user waiting time.Regional node cooperation is adopted to expand the cache space and to support the regional preference of cache content.Compared with the classical substitution algorithm,simulation results show that the algorithm in this paper has higher cache hit ratio and higher space utilization.

关键词： cache resource allocation blockchain-enabled iot edge computing Markov chain hierarchical caching technique

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Adjoining Batch markov Arrival Processes of a Markov chain

引用

Acta Mathematicae Applicatae Sinica 2018年第1期34卷 1-10页

作者： Xiao-yun MO Xu-yan XIANG Xiang-qun YANG College of Mathematics and Statistics Hunan University of Finance and Economics Changsha 410205 China College of Mathematics and Computational Science Hunan University of Arts and Science Changde 415000 China Key Laboratory of High performance Computing and Stochastic Information Processing Ministry of Education of China College of Mathematics and Computer Science Hunan Normal University Changsha 410081 China Hunan Province Cooperative Innovation Center for the Construction and Development of Dongting Lake Ecological Economic Zone Changde 415000 China

A batch markov arrival process（BMAP） X^＊=（N, J） is a 2-dimensional markov process with two components, one is the counting process N and the other one is the phase process J. It is proved that the phase process is a time-homogeneous Markov chain with a finite state-space, or for short, Markov chain. In this paper,a new and inverse problem is proposed firstly： given a Markov chain J, can we deploy a process N such that the 2-dimensional process X^＊=（N, J） is a BMAP？ The process X^＊=（N, J） is said to be an adjoining BMAP for the Markov chain J. For a given Markov chain the adjoining processes exist and they are not unique. Two kinds of adjoining BMAPs have been constructed. One is the BMAPs with fixed constant batches, the other one is the BMAPs with independent and identically distributed（i.i.d） random batches. The method we used in this paper is not the usual matrix-analytic method of studying BMAP, it is a path-analytic method. We constructed directly sample paths of adjoining BMAPs. The expressions of characteristic（D_k, k = 0, 1, 2· · ·）and transition probabilities of the adjoining BMAP are obtained by the density matrix Q of the given Markov chain J. Moreover, we obtained two frontal Theorems. We present these expressions in the first time.

关键词： Markov chain batch markov arrival process （BMAP） adjoining BMAP fixed constant batch independent identically distributed （i.i.d） random batch

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Consensus protocol for heterogeneous multi-agent systems: A Markov chain approach

引用

Chinese Physics B 2013年第1期22卷 569-573页

作者：朱善迎陈彩莲关新平 Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education

This paper deals with the consensus problem for heterogeneous multi-agent systems. Different from most existing consensus protocols, we consider the consensus seeking of two types of agents, namely, active agents and passive agents. The objective is to directly control the active agents such that the states of all the agents would achieve consensus. In order to obtain a computational approach, we subtly introduce an appropriate Markov chain to cast the heterogeneous systems into a unified framework. Such a framework is helpful for tackling the constraints from passive agents. Furthermore, a sufficient and necessary condition is established to guarantee the consensus in heterogeneous multi-agent systems. Finally, simulation results are provided to verify the theoretical analysis and the effectiveness of the proposed protocol.

关键词： heterogeneous multi-agent system consensus protocol Markov chain

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

On First Returning Time and Last Exit Time of a Class of Markov chain

引用

Acta Mathematica Sinica,English Series 2013年第2期29卷 331-344页

作者： Hui Zeng ZHANG Min Zhi ZHAO Lei WANG Department of Mathematics Hangzhou Normal University Department of Mathematics Zhejiang University

Let {Xn} be a Markov chain with transition probability pij =： aj-（i-1）＋,i,j ≥ 0, where aj=0 providedj 〈 0, a0 〉 0, a0＋a1〈 1 and ∑∞n=0 an= 1. Let μ∑∞n=1nan. It is known that {Xn} is positive recurrent when μ 〈 1; is null recurrent when μ= 1; and is transient when μ 〉 1. In this paper, the integrability of the first returning time and the last exit time are discussed. Keywords Geom/G/1 queuing model, first returning time, last exit time, Markov chain

关键词： Geom/G/1 queuing model first returning time last exit time Markov chain

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Markov chain-based Degree Distributions of Evolving Networks

引用

Acta Mathematica Sinica,English Series 2012年第10期28卷 1981-1994页

作者： Xiang Xing KONG Zhen Ting HOU Ding Hua SHI Quan Rong CHEN Qing Gui ZHAO School of Mathematics Central South University Department of Mathematics Shanghai University Department of Electronic Engineering City University of Hong KongP.R.China Department of Mathematics and Science Hunan First Normal University

In this paper, we study a class of stochastic processes, called evolving network Markov chains, in evolving networks. Our approach is to transform the degree distribution problem of an evolving network to a corresponding problem of evolving network Markov chains. We investigate the evolving network Markov chains, thereby obtaining some exact formulas as well as a precise criterion for determining whether the steady degree distribution of the evolving network is a power-law or not. With this new method, we finally obtain a rigorous, exact and unified solution of the steady degree distribution of the evolving network.

关键词： Evolving network Markov chain scale-free network degree distribution

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Continuous time Markov chain based website navigability measure

引用

The Journal of China Universities of Posts and Telecommunications 2011年第2期18卷 45-52页

作者： ZHANG Wei-feng LIU Xia ZHANG Ying-zhou ZHOU Guo-qiang State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China School of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China

Website navigability is acquiring a growing importance in website design and redesign,quality evaluation,and improvement.Existing navigability measures mainly depend on site link structure,so that they only consider the impact of site link structure for navigability and ignore the impact of Web page content.A continuous Markov chain model which depicts the user＇s surfing behavior can balance these two factors in the evaluation of website navigability,and it needs to estimate the page transition probabilities and user stay time according to user access log.In this way,we can obtain more reliable results for website navigability measure than the existed methods.Experiments show that our method is effective.

关键词： navigability measure Markov chain

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：