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Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 1,   Pages 85-89 doi: 10.1007/s11465-005-0023-6

Abstract:

A novel fuzzy clustering method based on chaos immune evolutionary algorithm (CIEFCM) is presentedamplitude is adjusted step by step, which greatly improves the colony diversity of the immune evolution algorithmdetect the fuzzy edge and exiguous edge but can evidently improve the searching efficiency of fuzzy clusteringalgorithm based on IEA.

Keywords： disturbance amplitude     disturbance     diversity     generation     processing    

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Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 313-316 doi: 10.1007/s11465-006-0026-y

Abstract: A multiobjective image recognition algorithm based on clustering Genetic Algorithm (GA), is proposedIn the evolutionary process of GA, a clustering method is provided that utilizes information from theThe whole population is grouped into different niches by the clustering method.Experimental results demonstrated that the number of target images could be determined by the algorithm

Keywords： clustering     different     recognition algorithm     Algorithm     multiobjective    

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The research of connectivity-credibility restricted clustering algorithm in wireless sensor networks

Yu Jiming,Sun Yamin,Lei Yanjing,Yang Yuwang

Strategic Study of CAE 2010, Volume 12, Issue 9,   Pages 73-77

Abstract:

This paper proposed a speeding clustering algorithm of connectivity-credibilityconstrained random dispose which based on some other clustering algorithms.Simulation shows that this algorithm can get large cover of clustering, logical distributing and goodComparing to the lowerst-ID clustering and highest-connectivity clustering algorithm, the algorithm canget less number of cluster-heads, more logical clustering, good communication between nodes and cluster-heads

Keywords： wireless sensor networks     connectivity-credibility     clustering algorithm    

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Efficient parallel implementation of a density peaks clustering algorithm on graphics processing unit Article

Ke-shi GE, Hua-you SU, Dong-sheng LI, Xi-cheng LU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 915-927 doi: 10.1631/FITEE.1601786

Abstract: The density peak (DP) algorithm has been widely used in scientific research due to its novel and effectivepeak density-based clustering approach.However, the DP algorithm uses each pair of data points several times when determining cluster centersIn this paper, we focus on accelerating the time-consuming density peaks algorithm with a graphics processingIn light of our analysis, we propose an efficient parallel DP algorithm targeting on a GPU architecture

Keywords： Density peak     Graphics processing unit     Parallel computing     Clustering    

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Robust Maximum Entropy Clustering Algorithm RMEC and Its Outlier Labeling

Deng Zhaohong,Wang Shitong,Wu Xisheng,Hu Dewen

Strategic Study of CAE 2004, Volume 6, Issue 9,   Pages 38-45

Abstract:

In this paper, the novel robust maximum entropy clustering algorithm RMEC, as the improved versionof the maximum entropy algorithm MEC, is presented to overcome its drawbacks: very sensitive to outliersCompared with algorithm MEC, the main contributions of algorithm RMEC exist in its much better robustness

Keywords： entropy     clustering     robustness     outliers     ε-insensitive loss function     weight factors    

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TIE algorithm: a layer over clustering-based taxonomy generation for handling evolving data None

Rabia IRFAN, Sharifullah KHAN, Kashif RAJPOOT, Ali Mustafa QAMAR

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 763-782 doi: 10.1631/FITEE.1700517

Abstract: A taxonomy incremental evolution (TIE) algorithm, as proposed, is a novel attempt to handle the dataIt serves as a layer over an existing clustering-based taxonomy generation technique and allows an existingThe algorithm was evaluated in research articles selected from the computing domain.It was found that the taxonomy using the algorithm that evolved with data needed considerably shorter

Keywords： Taxonomy     Clustering algorithms     Information science     Knowledge management     Machine learning    

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Smart optical-fiber structure monitoring based on granular computing

Guan LU, Dakai LIANG,

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 4,   Pages 462-465 doi: 10.1007/s11465-009-0073-2

Abstract: Using an optic fiber self-diagnosing system in health monitoring has become an important direction of smart materials and structure research. The buried optic fiber sensor can be used to test the parameters of the composite material. The granular computing method can reach the requirement of damage detection by analyzing digital signals and character signals of the smart structure at the same time. The paper investigates an optic fiber smart layer and presents a method for realizing optic fiber smart structure monitoring and damage detection by using granular computing. After the analysis, it is presumed that optic fiber smart structure monitoring based on granular computation can identify the damage from complex signals.

Keywords： smart material and structure     GrC     optical fiber sensor     rough set     clustering algorithm    

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A Comprehensive Approach for the Clustering of Similar-Performance Cells for the Design of a Lithium-Ion Article

Wei Li, Siqi Chen, Xiongbin Peng, Mi Xiao, Liang Gao, Akhil Garg, Nengsheng Bao

Engineering 2019, Volume 5, Issue 4,   Pages 795-802 doi: 10.1016/j.eng.2019.07.005

Abstract: , this work uses experimental and numerical methods to conduct a comprehensive investigation on the clusteringThe k-means clustering and support vector clustering (SVC) algorithms were then employed toExperimental verification of the results obtained from the clustering analysis was performed by measuring

Keywords： Clustering algorithm     Battery module     Equalization     Electric vehicle    

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Application of Fuzzy Pattern Recognition in the Measurement of Slurry Concentration

Li Dejun,Lv Runhua,Wang Runtian

Strategic Study of CAE 2007, Volume 9, Issue 5,   Pages 81-84

Abstract: Based on the fuzzy pattern recognition, data are sorted and further classified, with cooperative clusteringalgorithm.

Keywords： fuzzy pattern recognition     nearest neighbor(NN)     cooperative clustering algorithm(CCA)     slurry concentration    

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An anchor-based spectral clustering method None

Qin ZHANG, Guo-qiang ZHONG, Jun-yu DONG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1385-1396 doi: 10.1631/FITEE.1700262

Abstract:

Spectral clustering is one of the most popular and important clustering methods in pattern recognitionFor a clustering problem with n samples, it needs to compute the eigenvectors of the graph Laplacianmethods, i.e., power iteration clustering and landmark-based spectral clustering, on 10 real-world applicationsExperimental results show that ASC is consistently faster than the classical spectral clustering withcomparable clustering performance, and at least comparable with or better than the state-of-the-art

Keywords： Clustering     Spectral clustering     Graph Laplacian     Anchors    

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A systematic approach to ON-OFF event detection and clustering analysis of non-intrusive appliance load

Chuan Choong YANG,Chit Siang SOH,Vooi Voon YAP

Frontiers in Energy 2015, Volume 9, Issue 2,   Pages 231-237 doi: 10.1007/s11708-015-0358-6

Abstract: In this paper, a systematic approach to ON-OFF event detection and clustering analysis for NIALM wereThe goodness-of-fit (GOF) methodology is the event detection algorithm implemented.The results from the ON-OFF pairing algorithm were further clustered in groups utilizing the -meansclustering analysis.The -means clustering were implemented as an unsupervised learning methodology for the clustering analysis

Keywords： non-intrusive appliance load monitoring     event detection     goodness-of-fit (GOF)     K-means clustering    

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A sampling method based on URL clustering for fast web accessibility evaluation

Meng-ni ZHANG,Can WANG,Jia-jun BU,Zhi YU,Yu ZHOU,Chun CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 449-456 doi: 10.1631/FITEE.1400377

Abstract: In existing stratified sampling methods, however, all the pages in a website need to be analyzed for clusteringTo address this issue, we propose a novel page sampling method based on URL clustering for web accessibility

Keywords： Page sampling     URL clustering     Web accessibility evaluation    

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A Hierarchical-Based Initialization Method for K-Means Algorithm

Tang Jiubin,Lu Jianfeng,Tang Zhenmin, Yang Jingyu

Strategic Study of CAE 2007, Volume 9, Issue 11,   Pages 74-79

Abstract:

K-means algorithm is one of common clustering algorithms,  but the In this paper,  a hierarchical-based initialization approach is proposed for K-Means algorithm The general clustering problem is treated as weighted clustering problem,  the original data Then clustering is carried out at each level by top-down.and is insensitive to noise,  which is superior to some existing clustering algorithms.

Keywords： hierarchical technique     initial cluster centers     weighted data     K-means clustering    

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The research of grey clustering decision of assembly sequence based on petri net

Mo Qian,Luo Yi

Strategic Study of CAE 2008, Volume 10, Issue 11,   Pages 65-68

Abstract: certainly qualitative, fuzzy, non-numerical, assembly sequence is regarded as a gray system, and grey clusteringThis paper analyzes the gray classification of the influence factor and studies grey clustering decision

Keywords： assembly sequence     petri net     grey clustering decision method    

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Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge Research Articles

Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao,leyanfen@usst.edu.cn,hyao@usst.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 827-838 doi: 10.1631/FITEE.2000093

Abstract: We propose a novel algorithm based on the .The proposed algorithm can be divided into three steps, an offline phase at which an (AC) strategy isoffline fingerprint collection and similarity measurement, we employ an AC strategy based on the -medoids clusteringalgorithm using additional reference points that are geographically located at the outer cluster boundaryThe performance of the proposed algorithm is evaluated in two typical indoor environments, and compared

Keywords： 室内定位；接收信号强度（RSS）指纹；核岭回归；簇匹配；改进型分簇    

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Title Author Date Type Operation

Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge

Journal Article

Multiobjective image recognition algorithm in the fully automatic die bonder

JIANG Kai, CHEN Hai-xia, YUAN Sen-miao

Journal Article

The research of connectivity-credibility restricted clustering algorithm in wireless sensor networks

Yu Jiming,Sun Yamin,Lei Yanjing,Yang Yuwang

Journal Article

Efficient parallel implementation of a density peaks clustering algorithm on graphics processing unit

Ke-shi GE, Hua-you SU, Dong-sheng LI, Xi-cheng LU

Journal Article

Robust Maximum Entropy Clustering Algorithm RMEC and Its Outlier Labeling

Deng Zhaohong,Wang Shitong,Wu Xisheng,Hu Dewen

Journal Article

TIE algorithm: a layer over clustering-based taxonomy generation for handling evolving data

Rabia IRFAN, Sharifullah KHAN, Kashif RAJPOOT, Ali Mustafa QAMAR

Journal Article

Smart optical-fiber structure monitoring based on granular computing

Guan LU, Dakai LIANG,

Journal Article

A Comprehensive Approach for the Clustering of Similar-Performance Cells for the Design of a Lithium-Ion

Wei Li, Siqi Chen, Xiongbin Peng, Mi Xiao, Liang Gao, Akhil Garg, Nengsheng Bao

Journal Article

Application of Fuzzy Pattern Recognition in the Measurement of Slurry Concentration

Li Dejun,Lv Runhua,Wang Runtian

Journal Article

An anchor-based spectral clustering method

Qin ZHANG, Guo-qiang ZHONG, Jun-yu DONG

Journal Article

A systematic approach to ON-OFF event detection and clustering analysis of non-intrusive appliance load

Chuan Choong YANG,Chit Siang SOH,Vooi Voon YAP

Journal Article

A sampling method based on URL clustering for fast web accessibility evaluation

Meng-ni ZHANG,Can WANG,Jia-jun BU,Zhi YU,Yu ZHOU,Chun CHEN

Journal Article

A Hierarchical-Based Initialization Method for K-Means Algorithm

Tang Jiubin,Lu Jianfeng,Tang Zhenmin, Yang Jingyu

Journal Article

The research of grey clustering decision of assembly sequence based on petri net

Mo Qian,Luo Yi

Journal Article

Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge

Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao,leyanfen@usst.edu.cn,hyao@usst.edu.cn

Journal Article