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IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Li, Xuemei Geng, Yushui Yu, Kun Yang, Mengjie Qilu Univ Technol Shandong Acad Sci Sch Informat Jinan 250353 Shandong Peoples R China Qilu Univ Technol Shandong Acad Sci Grad Sch Jinan 250353 Shandong Peoples R China

ISBN: (纸本)9781538653739

cluster analysis has been widely used in many fields since its appearance, and the validation method of clustering has received much less attention. In fact, the quality evaluation of clustering results is also a crucial link in the whole clustering process. clustering validation are generally divided into external clustering validation, internal clustering validation and relative cluster validation. This paper studies the external clustering validation method. Firstly, the article selects several different categories of clustering verification methods. At the same time, the article introduces the Maclaurin symmetric mean (MSM) operator and multiple attribute decision making (MADM) method. Finally, an optimal clustering algorithm selection model for a certain data set can be obtained. The experimental results show that the proposed method can select the corresponding optimal algorithm for inhomogeneity data sets.

关键词： cluster algorithm External cluster validation MADM MSM operator

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The Application of clustering algorithm in Intrusion Detection System

The Application of Clustering Algorithm in Intrusion Detecti...

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Conference on the Future Computer and Control Systems

作者： Ge, Lei Zhang, CaiQian Kaifeng Univ Software Coll Kaifeng 475004 Henan Peoples R China

ISBN: (纸本)9783642293863

Intrusion is the use of unauthorized behavior, by scanning the loopholes in the system. access to user accounts, user file tampering. clustering is a clustering process, the clustering technique applied to intrusion detection in a supervised learning algorithm to overcome the requirements of the training set data in pure question mark, and can detect unknown intrusions. Discuss how the clustering algorithm is applied to intrusion detection and analysis of intrusion detection algorithm based on clustering problems.

关键词： intrusion detection cluster algorithm Information system

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Analysis and improvement for K-Means algorithm

Analysis and improvement for K-Means Algorithm

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1st International Conference on Mechanical Engineering

作者： Xiao Jing-zhong Xiao Li SW Univ Nationalities Sch Comp Sci & Technol Chengdu 610041 Peoples R China

ISBN: (纸本)9783037850770

K-Means algorithm is one of the mostly used foundation algorithm in data mining, it base on a greedy clustering algorithm. This paper will introduce this algorithm and analysis. Then prove the correctness of the algorithm. And then show the productivity of this algorithm. And at last, this paper will show some improvement to K-Means algorithm, including how to choose initial center points, and how to calculate the means. This will improve the algorithm at a certain extent.

关键词： K-Means cluster algorithm center point

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Energy Efficiency clustering algorithm in Wireless Sensor Network Application

Energy Efficiency Clustering Algorithm in Wireless Sensor Ne...

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5th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Cheng JianSheng Huaian Coll Informat Technol Dept Elect Engn Huaian 223003 Jiangsu Peoples R China

ISBN: (纸本)9781424436927

Wireless sensor networks have attracted much research attention in recent years and can be used in many different applications. In this paper we analyze the impact of Energy efficiency in Wireless sensor networks, as a result is clustering technique has been proven to be an effective approach for reducing energy consumption. It also can increase the scalability and lifetime of the network. we propose a novel cluster formation algorithm for wireless sensor networks according to considering the energy as an optimization parameter. Compared to other algorithms,the clustering algorithm increase the cluster head election mechanism, and the simulation results show that clustering algorithm achieves its intention of consuming less energy.

关键词： cluster algorithm Wireless sensor network energy efficiency

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A Bisecting K-Medoids clustering algorithm Based on Cloud Model

A Bisecting K-Medoids clustering Algorithm Based on Cloud Mo...

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16th IFAC Symposium on Information Control Problems in Manufacturing (INCOM)

作者： Sun, D. Fei, H. Li, Q. Shanghai Univ Sch Management Shanghai Peoples R China

In this study, an advanced K-Medoids clustering algorithm has been developed by using an auto-stopped bisecting scheme and replacing the traditional Euclidean distance by cloud similarity. The proposed algorithm is dedicated to cluster the users of Connected TV according to their behavior involved with connected TVs. According to the experimental results, the solutions obtained by the proposed algorithm are quite encouraging and the clustering results are much more stable than Euclidean-distance-based clustering method. The result shows that the proposed method has achieved good results in terms of cluster accuracy and time. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： cluster algorithm Connected TV user behavior bisecting K-Medoids cloud similarity

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Speaker recognition based on APSO-K-means clustering algorithm

Speaker recognition based on APSO-K-means clustering Algorit...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Sha, Man Yang, Huixian Xiangtan Univ Coll Informat Engn Xiangtan Hunan Peoples R China Xiangtan Univ Fac Mat & Photoelect Phys Xiangtan Peoples R China

ISBN: (纸本)9780769538167

In this paper, combined with ant colony algorithm, particle swarm optimization algorithm, K-means clustering algorithm, we propose an APSO-K-means clustering algorithm applied to speaker recognition. The algorithm utilizes the strong ability of the ant colony algorithm to process local extremum to avoid the sensitivity to local optimization of the PSO algorithm (APSO). Meanwhile, it utilizes APSO to guide the initialization of the cluster centers to improve the deficiency of the K-means clustering algorithm which depends on the initial value, which makes it easy to converge toward global optimality. The experiments in speaker recognition show that the new approach is better than the traditional method and effectively reduces the error recognition rate.

关键词： speaker recognition APSO algorithm K-means cluster algorithm

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Research on Mining of Government Data Based on Enhanced-Object Exchange Model 21

Research on Mining of Government Data Based on Enhanced-Obje...

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21st IEEE International Conference on Software Quality, Reliability and Security (QRS)

作者： Sa, Kejin Bai, Yu Wang, Chenggang Big Data Applicat Improving Govt Governance Capab Guiyang 550022 Peoples R China Harbin Engn Univ Coll Comp Sci & Technol Harbin 150001 Peoples R China Southwest China Inst Elect Technol Chengdu 610036 Peoples R China

ISBN: (纸本)9781665458139

In order to acquire the required knowledge from the vast amounts of government affairs data, accurate data mining has important practical significance. Therefore, a precision mining method of government affairs big data based on E-OEM model is studied. The method firstly uses web crawlers to capture the vast amounts of government data. Government data then performs data cleaning, pattern normalization, format standardization, index information collection and preprocessing, and finally, according to the purpose of data mining, the Kirkpatrick model is used to complete the mining effect evaluation. Experimental comparison specifically includes correlation analysis, cluster analysis, classification analysis, exception analysis and evolution analysis as well as five others. The results show that: compared with the three methods in previous studies, the Fl-score obtained by the application of the research method is higher (0.852), which proves that the quality of government affairs big data mining is better.

关键词： government affairs big data the data mining Kirkpatrick model cluster algorithm association rules

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Agent-based control system methodology for Reconfigurable Bending Press Machine 49th

Agent-based control system methodology for Reconfigurable Be...

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49th CIRP Conference on Manufacturing Systems (CIRP-CMS)

作者： Adenuga, Olukorede Tijani Mpofu, Khumbulani Kanisuru, Adeyeri Michael Tshwane Univ Technol Dept Ind Engn ZA-0001 Pretoria South Africa

In the present day technology creation, automation is a promising technology towards the achievement of constructive, innovative and sustainable designs and products in industry 4. The control system of machines that involves the application of mechatronic objects or intelligent units which are envisioned as building blocks for design of the systems are rather configured than being designed. In order to meet dynamic customer needs, within minimal time frames, thereby achieving short-time-to-market. The crucial element in this scenario is that the customer drives the pace and direction of the manufacturing entity. The reality of the matter is that the manufacturer needs to produce customer-centric designed products, and this may be achieved through the use of machinery and a system configured to satisfy the need. Realizing this scenario, in this article, an automated agent-based control system methodology (ACSME) has been proposed for Reconfigurable Bending Press Machine (RBPM) application due to ongoing research. The proposed methodology will help manufacturer of RBPM to address the need for more flexible control systems and to demonstrate their industrial flexibility in several reconfigurable machines applications. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： cluster algorithm Agent-based Approach Agent-based Control System Methodology (ACSME) Reconfigurable Bending Press Machine (RBPM)

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Binary tree summation Monte Carlo simulation for Potts models

Binary tree summation Monte Carlo simulation for Potts model...

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2nd APCTP/6th Taiwan International Symposium on Statistical Physics

作者： Wang, JS Natl Univ Singapore Singapore MIT Alliance Singapore 119260 Singapore Natl Univ Singapore Dept Computat Sci Singapore 119260 Singapore

In this talk, we briefly comment on Sweeny and Gliozzi methods. cluster Monte Carlo method, and recent transition matrix Monte Carlo for Potts models. We mostly concentrate on a new algorithm known as 'binary tree summation'. Some of the most interesting features of this method will be highlighted-such as simulating fractional number of Potts states, as well as offering the partition function and thermodynamic quantities as functions of temperature in a single run. (C) 2003 Elsevier Science B.V. All rights reserved.

关键词： Sweeny algorithm Gliozzi algorithm cluster algorithm binary tree summation Ising model

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cluster MONTE CARLO algorithmS IN STATISTICAL MECHANICS

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International Journal of Modern Physics C 1992年第1期3卷 209-212页

作者： JIAN-SHENG WANG Institut für Physik Universität Mainz D-6500 Mainz F.R. Germany Address after August 1991: Department of Physics Hong Kong Baptist College Kowloon Hong Kong.

The cluster Monte Carlo method, where variables are updated in groups, is very efficient at second order phase transitions. Much better results can be obtained with less computer time. This article reviews the method ... 详细信息

关键词： Monte Carlo simulation cluster algorithm Critical slowing down

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