This paper studies clustering load balance and routing protocol in Wireless Sensor Networks (WSNs). After improve RDCA clustering algorithm, we present a Two-Layered clustering-Based MultiHop Routing Protocol (TLCBMH)...
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ISBN:
(纸本)9781479938599
This paper studies clustering load balance and routing protocol in Wireless Sensor Networks (WSNs). After improve RDCA clustering algorithm, we present a Two-Layered clustering-Based MultiHop Routing Protocol (TLCBMH). Unlike RDCA, TLCBMH uses two different communication radiuses, low radius and high radius. Low radius is the cluster radius. High radius is the transmission power radius which cluster heads use to search for spare cluster heads. High radius is double of low radius. That fits more application environment of WSNs. After the clustering, cluster heads in RDCA communicate direct with the base station. The cluster heads in TLCBMH access to the base station through multihop. It deals with failed nodes at the initialization period of every work round, which makes WSNs more robust. Compared with RDCA, network simulation proves TLCBMH does not loss any clustering ability. However, it promotes WSNs average lifetime.
In breast cancer studies. researchers often use clustering algorithms to investigate similarity/dissimilarity among different cancer cases. The clustering algorithm design becomes a key factor to provide intrinsic dis...
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In breast cancer studies. researchers often use clustering algorithms to investigate similarity/dissimilarity among different cancer cases. The clustering algorithm design becomes a key factor to provide intrinsic disease information. However, the traditional algorithms do not meet the latest multiple requirements simultaneously for breast cancer objects. The Variable parameters, Variable densities, Variable weights, and Complicated Objects clustering algorithm (V3COCA) presented in this paper can handle these problems very well. The V3COCA (1) enables alternative inputs of none or a series of objects for disease research and computer aided diagnosis;(2) proposes an automatic parameter calculation strategy to create Clusters with different densities;(3) enables noises recognition, and generates arbitrary Shaped Clusters: and (4) defines a flexibly weighted distance for measuring the dissimilarity between two complicated medical objects, which emphasizes certain medically concerned issues in the objects. The experimental results with 10,000 patient cases from SEER database show that V3COCA can not only meet the various requirements of complicated Objects clustering, but also be as efficient as the traditional clustering algorithms. (C) 2008 Elsevier B.V. All rights reserved.
Aiming at the problem of load balancing and lifetime prolonging for wireless sensor networks (WSNs), and considering complex uncertainties existed in WSNs, this paper proposes a clustering routing protocol CRT2FLACO f...
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ISBN:
(纸本)9781479920747
Aiming at the problem of load balancing and lifetime prolonging for wireless sensor networks (WSNs), and considering complex uncertainties existed in WSNs, this paper proposes a clustering routing protocol CRT2FLACO for WSN based on type-2 fuzzy logic and ant colony optimization (ACO). Specifically, in the cluster set-up phase, a type-2 Mamdnai fuzzy logic system (T2MFLS) is built to handle rule uncertainty better and balance the network load, in which three important factors - residual energy, the number of neighbor nodes and the distance to the base station (BS) of a node - are considered as inputs, and the probability of the node to be a candidate cluster head (CH) and the CH competition radius as outputs of our T2MFLS, to select the final CHs;in the steady-state phase, in order to reduce the transmission consumption, all the CHs are linked into a chain using ACO algorithm, then each CH send its data packet to the leader along link, which is a CH eventually transmitting packets to the BS. The simulation results show that the proposed routing protocol can effectively balance network load and reduce the transmission energy consumption of CHs, thus greatly prolong the lifetime of WSN.
clustering algorithms are used in the analysis of gene expression data to identify groups of genes with similar expression patterns. These algorithms group genes with respect to a predefined dissimilarity measure with...
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clustering algorithms are used in the analysis of gene expression data to identify groups of genes with similar expression patterns. These algorithms group genes with respect to a predefined dissimilarity measure without using any prior classification of the data. Most of the clustering algorithms require the number of clusters as input. and all the objects in the dataset are usually assigned to one of the clusters. We propose a clustering algorithm that finds clusters sequentially, and allows for sporadic objects, so there are objects that are not assigned to any cluster. The proposed sequential clustering algorithm has two steps. First it finds candidates for centers of clusters. Multiple candidates are used to make the search for clusters more efficient. Secondly, it conducts a local search around the candidate centers to find the set of objects that defines a cluster. The candidate clusters are compared using a predefined score, the best cluster is removed from data, and the procedure is repeated. We investigate the performance of this algorithm using simulated data and we apply this method to analyze gene expression profiles in a study on the plasticity of the dendritic cells. (c) 2008 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.
In this paper we present a new multilevel clustering algorithm for Vehicular Ad-Hoc Networks (VANET), which we call the Density Based clustering (DBC). Our solution is focused on the formation of stable, long living c...
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In this paper we present a new multilevel clustering algorithm for Vehicular Ad-Hoc Networks (VANET), which we call the Density Based clustering (DBC). Our solution is focused on the formation of stable, long living clusters. Cluster formation is based on a complex clustering metric which takes into account the density of the connection graph, the link quality and the road traffic conditions. The tests performed in the simulation environment composed of VanetMobiSim and Java in Simulation Time (JiST)/SWANS have shown that DBC performs better than the popular approach (the Lowest Id algorithm)-the clusters stability has been significantly increased.
Modern distance education is a new Web-based form of education. Enhancing personalized teaching standard of distance learning site is an important and difficult research in the development of modern distance education...
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ISBN:
(纸本)9780769535579
Modern distance education is a new Web-based form of education. Enhancing personalized teaching standard of distance learning site is an important and difficult research in the development of modern distance education. Based on rough set (RS), Web learners clustering model, learning features reduction and clustering algorithm are presented, which provides a basis of personalized teaching strategies for distance learning website. Further research is to mine an process the dynamic personality of learner's knowledge, and then to provide services on achieving real-time personalized teaching requirement.
Among the bio-inspired techniques, PSO-based clustering algorithms have received special attention. An improved method named Particle Swarm Optimization (PSO) clustering algorithm based on cooperative evolution with m...
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Among the bio-inspired techniques, PSO-based clustering algorithms have received special attention. An improved method named Particle Swarm Optimization (PSO) clustering algorithm based on cooperative evolution with multi-populations was *** adopts cooperative evolutionary strategy with multi-populations to change the mode of traditional searching optimum solutions. It searches the local optimum and updates the whole best position (gBest) and local best position (pBest) ceaselessly. The gBest will be passed in all sub-populations. When the gBest meets the precision, the evolution will terminate. The whole clustering process is divided into two stages. The first stage uses the cooperative evolutionary PSO algorithm to search the initial clustering *** second stage uses the K-means algorithm. The experiment results demontrate that this method can extract the correct number of clusters with good clustering quality compared with the results obtained from other clustering algorithms.
From the point of view of modern educational technology development, the development process CAI from single computer to network is introduced. Through the induction of learning theory and education theory in differen...
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ISBN:
(纸本)9780769539362
From the point of view of modern educational technology development, the development process CAI from single computer to network is introduced. Through the induction of learning theory and education theory in different stages, the modern CAI and its main development mode are analyzed. Combining with computer software technology and network technology development, the system design of an open CAI platform is put forward. Using the network platform, the basic concepts and theories requirements of modern education theory and learning theory are realized. Using clustering algorithm and rough set theory, the application of network learning theory and design principle in CAI is studied. The results show that, with the continuous development of network technology, application of network learning theory and design principle in the fields of CAI will play an increasingly important role. In conclusion, in the near future, a truly mature and open learning environment will be able to build to achieve the greatest range of educational resources sharing, which makes the popularity of CAI into reality.
作者：
Zhang YihuaJimei Univ
Coll Business Adm Dept Informat Management Xiamen 361021 Fujian Peoples R China
In possession of great customer-data, Mobile Enterprise must transform data advantage into competitive advantage, which is not only to maximize income, but also to enhance the management system of channel. In this pap...
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ISBN:
(纸本)9781424435197
In possession of great customer-data, Mobile Enterprise must transform data advantage into competitive advantage, which is not only to maximize income, but also to enhance the management system of channel. In this paper, I applied the theory of cluster analysis to discuss the use of the cluster analysis technology in the mobile market segmentation field, and by integrating the basic-data I utilized the mobile improvement K-means to set up a channel subsection model in rural areas in order to divide the rural mobile market effectively.
In this paper, a clustering algorithm based on the immune mechanism of the capture of antigen by the antibody has been presented. The datum to be clustered are viewed as antigens,and the cluster centers are viewed as ...
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ISBN:
(纸本)9780769536040
In this paper, a clustering algorithm based on the immune mechanism of the capture of antigen by the antibody has been presented. The datum to be clustered are viewed as antigens,and the cluster centers are viewed as the antibodies in the immune system. The clustering is effectively the process in which the immune system constantly generates antibodies for the recognition of the antigens and finally generates the optimal antibodies for the capture of the antigens. The experimental results show that the algorithm can successfully be applied to the data clustering.
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