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检索条件"主题词=Clustering algorithm"

共 1889 条记录，以下是221-230 订阅

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A clustering algorithm for Detecting and Handling Black Hole Attack in Vehicular Ad Hoc Networks

引用

Europe, Middle East and North Africa Conference on Technology and Security to Support Learning (EMENA-TSSL)

作者： Cherkaoui, Badreddine Beni-hssane, Abderrahim Erritali, Mohammed Chouaib Doukkali Univ Fac Sci Dept Comp Sci LAROSERI Lab El Jadida Morocco Univ Sultan Moulay Slimane Fac Sci & Tech Dept Comp Sci TIAD Lab Beni Mellal Morocco

ISBN: (纸本)9783319465685;9783319465678

A vehicular ad hoc network (VANET) basically consists of a group of vehicles that communicate with each other through a wireless transmission and requires no pre-existing management infrastructure. This communication, as the main objective, streamlining traffic for drivers. This exchange of information is not always reliable because of several constraints such as the existence of malicious users aimed falsifying information to serve their own interests. In this paper, we will simulate the Black Hole attack in a VANET environment with a generated real world mobility model using MOVE Tool and SUMO and analyse the performance of this communication under this attack. And then we propose a clustering algorithm to detect and react against the black hole attacker node.

关键词： VANET Black hole attack Mobility model NS2 clustering algorithm

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Research on Balanced Energy Consumption of Wireless Sensor Network Nodes Based on clustering algorithm

Research on Balanced Energy Consumption of Wireless Sensor N...

引用

International Conference on Computer Network, Electronic and Automation (ICCNEA)

作者： Huang, Jie Hezhou Univ Coll Informat & Commun Engn Hezhou Peoples R China

ISBN: (纸本)9781538639818

A multi-cluster-head based clustering routing algorithm is researched and realized in order to achieve better balance the energy consumption of wireless sensor network nodes as well as promote the stability and extend the service life of the network. By taking cluster as the basic unit, it divides the wireless sensor network into multiple clusters, each of which includes a main cluster head node, an assistant cluster head node, a cluster management node and several ordinary nodes. The article elaborates the energy consumption model of the wireless sensor network, the network topological structure of the multi-cluster-head based clustering routing algorithm and the method for realization. In addition, it conducts simulation and analysis on the multi-cluster-head based clustering routing algorithm. According to the results, the algorithm can achieve preferable balance on energy consumption of various nodes in the wireless sensor network, which effectively extends the service life and improves the stability of the wireless sensor network. It has good application prospects.

关键词： Wireless sensor network Balanced energy consumption clustering algorithm Multi-cluster-head Data fusion

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Applied Biological Data Mining Based on Improved K-means clustering algorithm And KNN Classifier in Protein Sub-cellular Localization 7

Applied Biological Data Mining Based on Improved K-means Clu...

引用

7th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Lei, Zhenfeng Wang, Shunfang Yunnan Univ Sch Informat Sci & Engn Kunming 650504 Peoples R China

ISBN: (纸本)9781467399043

With the completion of the human genome sequencing, a large number of data especially amino acid sequences floods into biological database, How to analyze these data quickly and even predict the structure and function of protein correctly have become hot topics in recent years, In this paper, we mainly study K-means clustering algorithm and KNN classifier in amino acid sequences of complicated data, which are applied in the prediction of protein sub-cellular localization. In many cases, fuzzy boundary and unbalance are frequently appeared among biological data. The accuracy will be lower, if we make a prediction through traditional KNN and K-means clustering algorithm directly. Firstly, in order to make clear the unbalance, we propose the within-class thought to make sure that training samples in each class around the testing sample are selected and we introduce membership to tell which class the testing sample belongs to. Then, we bring in rough sets and membership to solve the fuzzy boundary. Particularly, we apply correlation coefficient in the rough sets to better reflect the relationship among data objects. The experimental results based on protein sub-cellular localization prediction show that the methods proposed newly better work than the traditional methods.

关键词： data mining clustering algorithm classification algorithm protein sub-cellular localization

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Dimension Reduction Using clustering algorithm and Rough Set Theory

Dimension Reduction Using Clustering Algorithm and Rough Set...

引用

3rd International Conference on Swarm, Evolutionary and Memetic Computing (SEMCCO)

作者： Sengupta, Shampa Das, Asit Kumar MCKV Inst Engn Dept Informat Technol Howrah 711204 W Bengal India Bengal Engn & Sci Univ Dept Comp Sci & Tech Sibpur 711103 W Bengal India

ISBN: (纸本)9783642353796;9783642353802

In real world, datasets have large number of attributes but few are important to describe them properly. The paper proposes a novel dimension reduction algorithm for real valued dataset using the concept of Rough Set Theory and clustering algorithm to generate the reduct. Here, projection of dataset based on two conditional attributes C-i and C-j is taken and K-means clustering algorithm is applied on it with K = number of distinct values of decision attribute D of the dataset to obtain K clusters. Also the dataset is clustered into K-groups using Indiscernibility relation applied on the decision attribute D. Then the connecting factor k of combined conditional attributes (C-i C-j) with respect to D is calculated using two cluster sets and attribute connecting set ACS = {(CiCj ->(K) is an element of D) for all C-i, C-j is an element of C, Conditional attribute set, and D (Decision attribute)} is formed. Each element (CiCj ->(k) D). ACS implies that Ci and Cj connecting together partition the objects that yields ( k* 100) % similar partitions as made on D. Now an undirected weighted graph with weights as the connecting factor k is constructed using attribute connecting set ACS. Finally based on the weight associated with edges, the important attributes, called reduct are generated. Experimental result shows the efficiency of the proposed method.

关键词： Dimension Reduction clustering algorithm Rough Set Theory Attribute Similarity Indiscernibility Relation Undirected weighted graph

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A Delay-Based clustering algorithm for Wireless Sensor Networks

A Delay-Based Clustering Algorithm for Wireless Sensor Netwo...

引用

International Workshop on Computer Science for Environmental Engineering and EcoInformatics (CSEEE)

作者： Shang, Fengjun Ren, Donghai Chongqing Univ Posts & Telecommun Coll Comp Sci & Technol Chongqing 400065 Peoples R China

ISBN: (纸本)9783642226939

In order to prolong the network lifetime, energy-efficient routing protocols should be designed to adapt the characteristic of wireless sensor networks. clustering algorithm is a kind of key technique used to reduce energy consumption. which can make a longer life span of sensor network. A clustering algorithm based on timer mechanism (CATM) was presented. By means of timer mechanism, it can guarantee the node with high remaining energy be chosen as the cluster heads node in priority in each round. Meanwhile, a aggregate of nodes that have received cluster heads information is preserved so that the algorithm is able to ensure that obtain a constant number of cluster heads and cluster heads are well scattered. Simulation results demonstrate that CATM algorithm effectively balances the energy dispatch of the sensors and obvious improvement on the network lifetime.

关键词： Wireless sensor networks clustering algorithm Timer

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Power backup Density based clustering algorithm for Maximizing Lifetime of Wireless Sensor Networks 4

Power backup Density based Clustering Algorithm for Maximizi...

引用

4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE)

作者： Wagh, Sanjeev Prasad, Ramjee Univ Pune KJ Coll Engn & Mgmt Res Pune Maharashtra India Aalborg Univ Ctr TeleInfrastruktur CTIF Aalborg Denmark

ISBN: (纸本)9781479946235

WSNs consists several nodes spread over experimental fields for specific application temporarily. The spatially distributed sensor nodes sense and gather the information for intended parameters like temperature, sound, vibrations, etc for the particular application. In this paper, we evaluate the impact of different algorithms i.e. clustering for densely populated field application, energy backup by adding energy harvesting node in field, positioning energy harvesting node smartly in the field and also positioning the base station in sensor field to optimize the communication between cluster head and base station. The analysis and simulation results justifies that availability of power backup for cluster nodes using energy harvesting and positioning the energy harvesting node and also base station enhance the lifetime of sensor network fields. WSN with power backup density based clustering algorithm can be applied for many sensitive applications like military for hostile and remote areas or environmental monitoring where human intervention is not possible.

关键词： Wireless sensor networks clustering algorithm Network lifetime Energy harvesting nodes

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Research hotspot and evolution trend analysis of TCM talent training based on clustering algorithm 24

Research hotspot and evolution trend analysis of TCM talent ...

引用

1st International Conference on Image Processing Machine Learning and Pattern Recognition

作者： Liang, Zhongyi Zhang, Xinyue Fu, Yuxin Zhao, Ziwei Wang, Ke Yu, Ning Changchun Univ Tradit Chinese Med Changchun Peoples R China Jilin Inst Drug Control Changchun Peoples R China State Adm Tradit Chinese Med Accreditat Ctr TCM Physician Beijing Peoples R China

ISBN: (纸本)9798400707032

This paper uses TF-IDF and Kleinberg algorithms to map the literature in the field of TCM talent training included in the core journals of CNKI from 2014 to 2024 from the number of publications, publishing organization, keyword clustering and mutation, analyze the research hot spots and evolution trends in the field of TCM talents in China, and draw research conclusions and put forward suggestions. The number of published articles is increasing year by year, which can strengthen the exchange, cooperation and resource sharing among research institutions, and emerge high hot topics such as traditional Chinese medicine culture, innovative talents, teacher education, innovation and entrepreneurship education. It is suggested to break the traditional shackles, innovate the training mode of TCM talents, and improve the quality and level of training. In-depth study of the talent training system, teaching methods, evaluation system and other key issues, and constantly innovate the education mode and training mechanism.

关键词： traditional Chinese medicine talent training TF-IDF Kleinberg clustering algorithm

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An Energy-Efficient clustering algorithm in Wireless Sensor Networks

An Energy-Efficient Clustering Algorithm in Wireless Sensor ...

引用

4th IEEE Conference on Industrial Electronics and Applications

作者： Zhao, Honggang Shi, Haoshan Tang, Haoyang Northwestern Polytech Univ Coll Elect Informat Xian 710072 Peoples R China

ISBN: (纸本)9781424427994

Reducing node energy consumption is a vital requirement in wireless sensor networks. In this paper, we studied classic clustering algorithms in wireless sensor networks and find two main reasons causing unnecessary energy consumption, which are fixed operation periods and too much information exchanged in cluster-heads selection. Then a more energy-efficient clustering algorithm is proposed, whose kernels are adaptive operation period model and a new cluster-heads selection method. Simulation results show that the proposed protocol is more energy-efficient and suitable for wireless sensor network.

关键词： adaptive period virtual grid residual energy clustering algorithm wireless sensor network

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An Energy-efficient clustering algorithm for Data Gathering and Aggregation in Sensor Networks

An Energy-efficient Clustering Algorithm for Data Gathering ...

引用

4th IEEE Conference on Industrial Electronics and Applications

作者： Liang, Ying Gao, Hongwei Shenyang Ligong Univ Sch Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781424427994

Energy-efficient data gathering is a common but critical operation in many applications of wireless sensor networks. clustering is a kind of key technique used to reduce energy consumption, which can decrease the communication load and prolong the network lifetime by means of similar data aggregation in the cluster-heads. In this paper, we propose a novel clustering algorithm which better suit the periodical data gathering applications. Our approach first use genetic algorithm to partition the adjacent nodes which will sense similar target into one cluster, then elects cluster-heads with more residual energy and fewer intra-cluster communication cost. Since improving the rate of data aggregation in clusters, our approach can effectively reduce redundant data transmission and the whole energy consumed in the network. Our experimental results demonstrate that the proposed algorithms significantly outperform previous methods, in terms of system lifetime.

关键词： wireless sensor network clustering algorithm information similarity data aggregation genetic algorithm

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Acquaint based grid clustering algorithm for Underwater wireless sensor network

Acquaint based grid clustering algorithm for Underwater wire...

引用

International Conference on Information Communication and Embedded Systems (ICICES)

作者： Sundarameena, V. Priyatharisini, D. Manakula Vinayagar Inst Technol Dept CSE Pondicherry India

ISBN: (纸本)9781479938346

Underwater wireless sensor network (UWSN) is an important emerging research area in wide range of application, unlike the terrestrial network it uses the acoustic signal which has a unique characteristics like limited bandwidth, high and variable propagation delay, transmit energy, minimum network lifetime and so on. This paper proposes an efficient clustering algorithm having 3D-GRID network architecture and it uses limited control information for data gathering to improve the energy efficiency of the network. The GRID clustering method supports 3D deployment based on geographical location of the sensors which has cluster heads (CH) and non cluster heads (NCH). All the cluster heads are present in the center of the network and all the non-cluster head nodes are in minimum distance to the cluster head. This network structure helps to avoid the control packets for intra communication. For inter communication the CH data packet contains the control packet for route establishment and data transmission. Thus this technique reduce the usage of energy while communication and improve the lifetime of the network.

关键词： UWSN Acoustic Signal clustering algorithm GRID network architecture

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