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A hormone-based clustering algorithm in wireless sensor networks

A hormone-based clustering algorithm in wireless sensor netw...

引用

2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010

作者： Dong, Dayuan You, Haifeng Zhang, Yipeng Wang, Xufa Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781424463503

Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper, we propose a hormone-based clustering algorithm (HCA) inspired by the communication mechanism of bio-endocrine system to prolong the lifetime of the sensor nodes. Two kinds of hormones, cluster hormone and member hormone, are used in the algorithm. Hormone message can promote a node to become a cluster head or a member node. Comparative experiment shows that the proposed algorithm has effectively prolong the lifetime of WSN compared with LEACH[1] and HEED[2]. © 2010 IEEE.

关键词： Clustering algorithms

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Quantitative and qualitative forecasting applied to supply-chain inventory

Quantitative and qualitative forecasting applied to supply-c...

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2010 2nd International Conference on MultiMedia and Information Technology, MMIT 2010

作者： Shao, Chenxi Wang, Lizhong Computer Science and Technology School of University of Science and Technology of China Hefei China Anhui Province Key Laboratory Software in Computing and Communication Hefei 230027 China MOE-Microsoft Key Laboratory Multimedia Computing and Communication University of Science and Technology of China Hefei China

ISBN: (纸本)9780769540085

In the process of supply chain (SC) management, time inventory management problem is extremely important. In terms of academic methods, quantitative methods are very popular as the researchers could calculate the inventory if they got the historic data of some SC. However, based on quantitative methods and the results cannot too be convincible. This paper considered a supply chain system includes several kinds of products. As to the historic suppliers' demand data of this SC system, firstly we applied a quantitative forecasting analysis method to it;secondly we made a qualitative analysis to improve the complex system's inventory management performance. According to the comparison between quantitative method and the method used in this paper, we find that the accuracy is more perfect. Not only the inventory cost is lower, also the forecasting accuracy is better. © 2010 IEEE.

关键词： Supply chain management

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A new boundary treatment method for SPH and application in fluid simulation

A new boundary treatment method for SPH and application in f...

引用

3rd International Conference on Information and computing, ICIC 2010

作者： Song, Bo Dong, Lanfang School of Computer Science and Technology USTC Hefei China Anhui Province Key Lab. of Software in Computing and Communication China

ISBN: (纸本)9780769540474

Appropriate dealing with boundary conditions is very important for SPH. Current boundary treatment methods like boundary force method, ghost particle method and virtual boundary layer method, when dealing with complex boundaries, they will have to compute much on putting external particles. For resolving this problem, we propose a new method assuming part of boundary surface instead of external particles, called effective force surface, directly repels the internal particles which approach sufficiently close. We call this new method EFS method. It is implemented in the SPH model for simulating fluid in rabbit-type cup and dam-breaking. In the former case, liquid flows vividly and no internal particles penetrate boundaries. In the latter case, the result is similar to existing result. The experimental results show that EFS method can effectively and precisely deal with complex boundary conditions. © 2010 IEEE.

关键词： Boundary conditions

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A novel updating strategy for associative memory scheme in cyclic dynamic environments

A novel updating strategy for associative memory scheme in c...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Cao, Yong Luo, Wenjian Nature Inspired Computation and Applications Laboratory School of Computer Science and Technology University of Science and Technology of China Hefei 230027 Anhui China Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei 230027 Anhui China

ISBN: (纸本)9781424463343

Associative memory schemes have been developed for Evolutionary Algorithms (EAs) to solve Dynamic Optimization Problems (DOPs), and demonstrated powerful performance. In these schemes, how to update the memory could be important for their performance. However, little work has been done about the associative memory updating strategies. In this paper, a novel updating strategy is proposed for associative memory schemes. In this strategy, the memory point whose associated environmental information is most similar to the current environmental information is first picked out from the memory. Then, the selected memory individual is updated according to the fitness value, and the associated environmental information is updated according to the matching degree between environmental information and individuals. This updating strategy is embedded into a stateof-the-art algorithm, i.e. the MPBIL, and tested by experiments. Experimental results demonstrate that the proposed updating strategy is helpful for associative memory schemes to enhance their search ability in cyclic dynamic environments.

关键词： Associative processing

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Scalable video multicast with joint layer resource allocation in broadband wireless networks

Scalable video multicast with joint layer resource allocatio...

引用

International Conference on Network Protocols

作者： Li, Peilong Zhang, Honghai Zhao, Baohua Rangarajan, Sampath Dept. of Computer Science and Technology University of Science and Technology of China China NEC Laboratories America United States State Key Laboratory of Networking and Switching Technology Beijing China Province Key Laboratory of Software in Computing and Communication Hefei Anhui 230027 China

ISBN: (纸本)9781424486458

Scalable video coding (SVC), together with adaptive modulation and coding (AMC), can improve wireless multicast streaming video by jointly performing radio resource allocation and modulation and coding scheme (MCS) selection. However, the existing schemes in the literature allocate radio resources for different video layers separately, which leads to a waste of radio resources. In this work, we introduce the notion of joint layer resource allocation which allows to jointly allocate resources to multiple video layers that are assigned the same MCS. We formulate this problem and prove it to be NP-hard. Then we develop a pseudo-polynomial algorithm that finds the optimal total system utility. Our algorithm assumes a very generic utility function and flexible video layer rates. To reduce the complexity of the algorithm, we also propose Fully Polynomial Time Approximation Schemes (FPTAS) for the same problem. Simulation results show that our optimal algorithm offers significant improvement on system utility over a previous optimal algorithm and a greedy algorithm both of which do not support joint layer resource allocation. The proposed approximation algorithm provides controllable tradeoff between performance and computational complexity and, with appropriately chosen parameters, it outperforms the greedy algorithm with 40% less running time. © 2010 IEEE.

关键词： Resource allocation

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Notice of Retraction: A hormone-modulated emotional model

Notice of Retraction: A hormone-modulated emotional model

引用

International Conference on Computer Engineering and Technology, ICCET

作者： Jianwei Liang Haifeng You Xufa Wang Department of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei China

This article has been retracted by the publisher.

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A Clustering System for Gene Expression Data Based upon Genetic Programming and the HS-Model

A Clustering System for Gene Expression Data Based upon Gene...

引用

The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Guiquan Liu Xiufang Jiang Lingyun Wen Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Cluster analysis is a major method to study gene function and gene regulation information for there is a lack of prior knowledge for gene data. Many clustering methods existed at present usually need manual operations or predetermined parameters, which are difficult for gene data. Besides, gene data possess their own characteristics, such as large scale, high-dimension, and noise. Therefore, a systematic clustering algorithm should be proposed to effectively deal with gene data. In this paper, a novel genetic programming (GP) clustering system for gene data based on hierarchical statistical model (HS-model) is proposed. And an appropriate fitness function is also proposed in this system. This clustering system can largely eliminate the infection of data scale and dimension. The proposed GP clustering system is applied to cluster the whole intact yeast gene data without dimensionality reduction. The experimental results indicate that the algorithm is highly efficient and can effectively deal with missing values in gene dataset

关键词： genetic programming cluster analysis missing value fitness function

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A fast algorithm for finding community structure based on community closeness

A fast algorithm for finding community structure based on co...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Xiufang Jiang Guiquan Liu Zhiting Lin Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Recently, the characterization of community structures in complex networks has received a considerable amount of attentions. Effective identification of these communities or clusters is a general problem in the field of data mining. In this paper we present a /ast hierarchical agglomerative algorithm based on community closeness (FHACC) algorithm, for detecting community structure which is very efficient and faster than many other competing algorithms. FHACC tends to agglomerate such communities that share the most common vertices into larger ones. Its running time on a sparse network with n vertices and m edges is O(mk + mt), where k denotes the mean vertex degree, and t is the iteration times of community agglomeration in FHACC algorithm. The algorithm was tested on several real-world networks and proved to be high efficient and effective in community finding.

关键词： community structure complex network data mining community closeness

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Interactive PBIL with Multiple Probability Vectors for Multimodal Optimization with Implicit Performance Indices

Interactive PBIL with Multiple Probability Vectors for Multi...

引用

2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Haifeng You Xufa Wang Department of Computer Science and Technology Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei China

ISBN: (纸本)9781424463473

Interactive population-based incremental learning (IPBIL) is an effective method to solve optimization problems with implicit performance indices. It can significantly reduce user fatigue compared with interactive evolutionary computation (IEC). However,each run of IPBIL can only find one solution or some similar solutions. Thus it is not suitable for multimodal optimization problems with implicit performance indices. To solve this problem,we propose an IPBIL with multiple probability vectors (IPBIL-MPV) in this work. The key idea is to utilize multiple probability vectors to catch different search directions and thus find more than one solutions. We perform a subjective experiment in which IPBIL-MPV is applied to a fashion design problem. The experimental results show that IPBIL-MPV can find several distinct solutions in a run. Thus it is an effective method to solve multimodal optimization problems with implicit performance indices.

关键词： population-based incremental learning multimodal optimization:implicit performance indices:fashion design

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A Hormone-based Clustering Algorithm in Wireless Sensor Networks

A Hormone-based Clustering Algorithm in Wireless Sensor Netw...

引用

2010 2nd International Conference on Computer Engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Dayuan Dong Haifeng You Yipeng Zhang Xufa Wang Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China HefeiChina

ISBN: (纸本)9781424463473;9781424463497;9781424463503

Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper,we propose a hormone-based clustering algorithm (HCA) inspired by the communication mechanism of bioendocrine system to prolong the lifetime of the sensor nodes. Two kinds of hormones,cluster hormone and member hormone,are used in the algorithm. Hormone message can promote a node to become a cluster head or a member node. Comparative experiment shows that the proposed algorithm has effectively prolong the lifetime of WSN compared with LEACH[1] and HEED[2].

关键词： hormone:clustering:wireless sensor networks

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