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Critical dynamics of two-replica cluster algorithms

INTERNATIONAL JOURNAL OF MODERN PHYSICS C 2001年第2期12卷 257-271页

作者： Li, XN Machta, J Univ Massachusetts Dept Phys Amherst MA 01003 USA

The dynamic critical behavior of the two-replica cluster algorithm is studied. Several versions of the algorithm are applied to the two-dimensional, square lattice Ising model with a staggered field. The dynamic exponent for the full algorithm is found to be less than 0.4. It is found that odd translations of one replica with respect to the other together with global flips are essential for obtaining a small value of the dynamic exponent.

关键词： cluster algorithm ising antiferromagnet critical dynamics

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Anomaly Detection algorithm Based on cluster of Entropy 13th

Anomaly Detection Algorithm Based on Cluster of Entropy

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13th CCF Conference on Computer Supported Cooperative Work and Social Computing (ChineseCSCW)

作者： Tan, Wenan Fang, Xi Zhao, Lu Tang, Anqiong Nanjing Univ Aeronaut & Astronaut Sch Comp & Technol Nanjing 210016 Peoples R China Shanghai Polytech Univ Sch Comp & Informat Shanghai 2012209 Peoples R China

ISBN: (纸本)9789811330445;9789811330438

To address the issue that the K-means algorithm chooses and determines the initial cluster center in a random way, which would fall into the local optimal clustering result, a way towards choosing the initial clustering center using information entropy is proposed. This proposed method divides the dataset evenly into data blocks with more than K, and then uses the entropy method to obtain the value of target function of each data block, as well as selects the centroid corresponding to the data block with the smallest value function of the first k target as the initial cluster center. By using entropy method to ensure the efficiency of the initial clustering center selection, an anomaly detection method is proposed. The result of the experiment show that this method performs better than the traditional K-means algorithm both in clustering effect and anomaly detection ability.

关键词： Anomaly detection Information entropy cluster algorithm cluster analysis

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Compiling the Programmed Load Spectrum of Machine Tools Based on ACER-Weibull Extrapolation Method and clustering algorithm

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JOURNAL OF TESTING AND EVALUATION 2025年第3期53卷

作者： Sun, Bo Hu, Wenting Deng, Chengyang Li, Qinghua Changchun Univ Sch Mech & Vehicle Engn 6543 Weixing Rd Changchun 130022 Jilin Peoples R China

The programmed load spectrum is an important foundation for reliability tests, reliability design, and life prediction. Because of the various working conditions and limited load information of machine tools, this characteristic needs to be fully considered when preparing the programmed load spectrum. In this article, a framework for compiling the programmed load spectrum of machine tools is established based on time-domain extrapolation and a clustering algorithm. First, the average conditional exceedance rate (ACER)-Weibull time-extrapolation method is proposed for load extrapolation. This method uses the average conditional exceedance rate method and the Weibull distribution to extrapolate the load above the maximum threshold and below the minimum threshold, respectively. Secondly, the *** clustering algorithm is used to divide the intervals of the programmed load spectrum, and the joint probability density function of the mean and amplitude is established using the Copula function. Finally, this framework is applied to compile the programmed load spectrum of computer numerical control lathes, and the cutting force spectrum is compiled, demonstrating the superiority of the proposed method.

关键词： load spectrum machine tools time extrapolation cluster algorithm Copula function

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Comparison of cluster algorithms for the Analysis of Text Data Using Kolmogorov Complexity

Comparison of Cluster Algorithms for the Analysis of Text Da...

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15th International Conference on Neuro-Information Processing

作者： Geweniger, Tina Schleif, Frank-Michael Hasenfuss, Alexander Hammer, Barbara Villmann, Thomas Univ Leipzig Dept Med D-04103 Leipzig Germany Tech Univ Clausthal Inst CS D-38678 Clausthal Zellerfeld Germany

ISBN: (纸本)9783642030390

In this paper we present a comparison of multiple cluster algorithms and their suitability for clustering text data. The clustering is based on similarities only, employing the Kolmogorov complexity as a similiarity measure. This motivates the set: of considered clustering algorithms which take into account the similarity between objects exclusively. Compared cluster algorithms are Median kMeans, Median Neural Gas, Relational Neural Gas, Spectral clustering and Affinity Propagation.

关键词： cluster algorithm similarity data neural gas spectral clustering message passing kMeans Kolmogorov complexity

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cluster algorithmS FOR NONLINEAR SIGMA MODELS

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International Journal of Modern Physics C 1992年第1期3卷 213-219页

作者： ULLI WOLFF CERN Theory Division CH-1211 Genève 23 Switzerland

Percolation cluster Monte Carlo algorithms for nonlinear σ-models on the lattice are reviewed with special emphasis on their possible generalizations. While they have been found to practically eliminate critical slowing down for the standard O(n) invariant vector models, their extension to other physically similar models — like RP n−1 and SU(n)×SU(n) chiral models — is less straight forward than one might have thought. I outline the present situation in this area of research. In the second part of my talk I described a numerical calculation of a physical running coupling constant in the O(3) model. This represents an application of the cluster technique in a preparatory study for a later lattice gauge theory calculation. This material can be found in Ref. 11.

关键词： Monte Carlo algorithm Critical Slowing Down cluster algorithm Sigma model

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cluster algorithmS FOR SURFACES

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International Journal of Modern Physics C 1992年第1期3卷 235-246页

作者： HANS GERD EVERTZ MARTIN HASENBUSCH MIHAIL MARCU KLAUS PINN SORIN SOLOMON Supercomputer Computations Research Institute Florida State University Tallahassee FL 32306 USA Fachbereich Physik Abt. Theoretische Physik Universität Kaiserslautern Postfach 3049 D-6750 Kaiserslautern Germany II. Institut für Theoretische Physik der Universität Hamburg Luruper Chaussee 149 2000 Hamburg 50 Germany School of Physica and Astronomy Raymond and Beverly Sackler Faculty of Exact Sciences Tel Aviv University 69978 Tel Aviv Israel Institut für Theoretische Physik I Universität Münster Wilhelm-Klemm-Str. 9 D-4400 Münster Germany Racah Institute of Physics Hebrew University 91904 Jerusalem Israel

We discuss a new cluster algorithm that completely eliminates critical slowing down for surface models of the SOS (solid-on-solid) type.

关键词： SOS models Critical slowing down cluster algorithm Kosterlitz-Thouless transition

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CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models

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COMPUTER PHYSICS COMMUNICATIONS 2014年第3期185卷 1038-1043页

作者： Komura, Yukihiro Okabe, Yutaka Japan Atom Energy Agcy Nucl Sci & Engn Directorate Tokai Ibaraki 3191195 Japan Tokyo Metropolitan Univ Dept Phys Hachioji Tokyo 1920397 Japan

We present sample CUDA programs for the GPU computing of the Swendsen-Wang multi-cluster spin flip algorithm. We deal with the classical spin models;the lsing model, the q-state Potts model, and the classical XY model. As for the lattice, both the 20 (square) lattice and the 3D (simple cubic) lattice are treated. We already reported the idea of the CPU implementation for 2D models (Komura and Okabe, 2012). We here explain the details of sample programs, and discuss the performance of the present CPU implementation for the 3D Ising and XY models. We also show the calculated results of the moment ratio for these models, and discuss phase transitions. Program summary Program title: SWspin Catalogue identifier: AERM_v1_0 Program summary URL: http://***/summaries/AERM_v1_*** Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://***/licence/*** No. of lines in distributed program, including test data, etc.: 5632 No. of bytes in distributed program, including test data, etc.: 14688 Distribution format: *** Programming language: C, CUDA. Computer: System with an NVIDIA CUDA enabled CPU. Operating system: System with an NVID1A CUDA enabled CPU. Classification: 23. External routines: NVIDIA CUDA Toolkit 3.0 or newer Nature of problem: Monte Carlo simulation of classical spin systems. Ising, q-state Potts model, and the classical XY model are treated for both two-dimensional and three-dimensional lattices. Solution method: GPU-based Swendsen-Wang multi-cluster spin flip Monte Carlo method. The CUDA implementation for the cluster-labeling is based on the work by Hawick et al. [1] and that by Kalentev et al. 121. Restrictions: The system size is limited depending on the memory of a CPU. Running time: For the parameters used in the sample programs, it takes about a minute for each program. Of course, it depends on the system size, the number of Monte Carlo s

关键词： Monte Carlo simulation cluster algorithm Ising model XY model Parallel computing GPU

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Using cluster algorithms with a machine learning technique and PMF models to quantify local-specific origins of PM2.5 and associated metals in Taiwan

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ENVIRONMENTAL POLLUTION 2023年第Part2期316卷

作者： Hsu, Chin -Yu Soo, Jhy-Charm Lin, Sheng-Lun Wu, Chih-Da Chi, Kai Hsien Hsu, Wen-Chang Tseng, Chun-Chieh Chen, Yu-Cheng Ming Chi Univ Technol Dept Safety Hlth & Environm Engn 84 Gungjuan Rd New Taipei Taiwan Ming Chi Univ Technol Ctr Environm Sustainabil & Human Hlth 84 Gungjuan Rd New Taipei Taiwan Georgia Southern Univ Jiann Ping Hsu Coll Publ Hlth Dept Biostat Epidemiol & Environm Hlth Sci Statesboro GA USA Beijing Inst Technol Sch Mech Engn Beijing Peoples R China Natl Hlth Res Inst Natl Inst Environm Hlth Sci 35 Keyan Rd Miaoli Taiwan Natl Cheng Kung Univ Dept Geomat Tainan Taiwan Natl Yang Ming Univ Inst Environm & Occupat Hlth Sci 1 Daxue Rd Tainan Taiwan Dahan Inst Technol Dept Civil Engn & Resource Management 1 Shuren St Xincheng Township 971 Hualien County Taiwan Tzu Chi Univ Dept Publ Hlth 701 Zhongyang Rd Hualien Hualien County Taiwan China Med Univ Dept Occupat Safety & Hlth 91 Hsueh Shih Rd Taichung Taiwan Kaohsiung Med Univ Res Ctr Environm Med Kaohsiung Taiwan

The influence of long-range transport (LRT) of air pollutants on neighboring regions and countries has been documented. The magnitude of LRT aerosols and related constituents can misdirect control strategies for local air quality management. In this study, we aimed to quantify PM2.5 (diameter less than 2.5 mu m, PM2.5) and associated metals derived from local sources and LRT in different geographic locations in Taiwan using advanced receptor models. We collected daily PM2.5 samples (n =similar to 1000) and analyzed 28 metals every three days from 2016 to 2018 in the northern, central-south, eastern, and southern areas of Taiwan. We first used a machine learning technique with a cluster algorithm coupled with a backward trajectory to classify local, regional, and LRT-related aerosols. We then quantified the source contributions with a positive matrix factorization (PMF) model for Taiwan weighted by region-specific populations. The northern and eastern regions were found to be more vulnerable to LRT-related PM(2.5 )and metals than the central-south and southern regions in Taiwan. The LRT increased Pb and As concentrations by 90-200% and similar to 40% in the northern and central-south regions. Ambient PM2.5-metals mainly originated from local traffic-related emissions in the northern, central-south, and southern regions, whereas oil combustion was the primary source of PM2.5-metals in the eastern region. By subtracting the influence from the LRT, the contributions of domestic emission sources to ambient PM2.5 metals in Taiwan were 35% from traffic-related emission, 17% from non-ferrous metallurgy, 13% from iron ore and steel factories, 12% from coal combustion, 12% from oil combustion, 10% from incinerator emissions, and < 1% from cement manufacturing emissions. This study proposed an advanced method for refining local source contributions to ambient PM2.5 metals in Taiwan, which provides useful information on regional control strategies.

关键词： Fine particle Metal Local emission cluster algorithm Receptor model

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CPA: A cluster-Based Packet Acknowledgement Approach in WSNs

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JOURNAL OF INTERNET TECHNOLOGY 2014年第2期15卷 203-214页

作者： Sun, Yun-Lei Qiao, Xiu-Quan Cheng, Bo Xue, Si-Da Chen, Jun-Liang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China China Univ Petr State Key Lab Networking & Switching Technol Beijing Peoples R China

In wireless sensor network, repairing packet loss lead to increasing of the network load and substantial energy consumption. In order to reduce the network load, most of transport protocols employ a Cumulative Acknowledgment (CACK) policy for received packets. In this paper, we propose a cluster-based Packet Acknowledgement (CPA) approach that naturally reduces more ACKs than traditional approaches of cumulating multi-packets of multi-nodes. A distributed greedy clustering algorithm is employed to form clusters with the minimum number. Different strategies are used to reduce the amount of packet ACKs in intra-cluster and inter-cluster respectively. And a scalable Bloom Filter is used to fix the length of the CACK, which can effectively save the storage. We also discuss a guarantee condition for the reduction of packet ACK path length. Our simulation results show that the CPA approach effectively increases the packet delivery ratio, and also reduces both the average end-to-end delay and the total length of ACKs, which thus decreases the network load.

关键词： Wireless sensor network Transport protocol cluster algorithm Bloom filter Packet delivery

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cluster dynamics and universality of Ising lattice gases

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 1998年第1-2期251卷 224-234页

作者： Heringa, JR Blote, HWJ Delft Univ Technol Lab Tech Nat Kunde NL-2600 GA Delft Netherlands

Lattice gases with nearest-neighbour exclusion are studied by means of Monte Carlo simulations with an efficient cluster algorithm. The critical dynamics is consistent with a dynamical exponent z = 0 in the case of Wolff-like cluster updates for square and simple-cubic lattices in the studied range of lattice sizes. We find the critical activity z(c) = 0.72020(4) for the body-centred cubic lattice. The critical exponents y(h) = 2.475(8) and y(t) = 1.61(6) disagree with an earlier study, but they do agree with the known values for the three-dimensional Ising universality class. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： lattice gas universality cluster algorithm percolation

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