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Artykuły w czasopismach na temat "Module clustering"
Alshareef, Haya, i Mashael Maashi. "Application of Multi-Objective Hyper-Heuristics to Solve the Multi-Objective Software Module Clustering Problem". Applied Sciences 12, nr 11 (2.06.2022): 5649. http://dx.doi.org/10.3390/app12115649.
Pełny tekst źródłaHou, Jie, Xiufen Ye, Chuanlong Li i Yixing Wang. "K-Module Algorithm: An Additional Step to Improve the Clustering Results of WGCNA Co-Expression Networks". Genes 12, nr 1 (12.01.2021): 87. http://dx.doi.org/10.3390/genes12010087.
Pełny tekst źródłaHu, Hai Yan, i You Qiao Zhang. "The Study and Realization of Energy-Aware Routing Algorithm of Wireless Sensor Networks". Applied Mechanics and Materials 201-202 (październik 2012): 767–72. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.767.
Pełny tekst źródłaKirve, Shraddha. "Clustering Techniques in Wireless Sensor Networks: A Practical Study". International Journal for Research in Applied Science and Engineering Technology 9, nr VI (10.06.2021): 536–38. http://dx.doi.org/10.22214/ijraset.2021.34990.
Pełny tekst źródłaKarayiannis, Dimitrios, i Spyros Tragoudas. "Clustering Network Modules with Different Implementations for Delay Minimization". VLSI Design 7, nr 1 (1.01.1998): 1–13. http://dx.doi.org/10.1155/1998/69289.
Pełny tekst źródłaMohammad Shahid, Sunil Gupta i MS. Sofia Pillai. "Machine Learning-Based False Positive Software Vulnerability Analysis". Global Journal of Innovation and Emerging Technology 1, nr 1 (15.06.2022): 29–35. http://dx.doi.org/10.58260/j.iet.2202.0105.
Pełny tekst źródłaStrauch, Martin, Jochen Supper, Christian Spieth, Dierk Wanke, Joachim Kilian, Klaus Harter i Andreas Zell. "A Two-Step Clustering for 3-D Gene Expression Data Reveals the Main Features of the Arabidopsis Stress Response". Journal of Integrative Bioinformatics 4, nr 1 (1.03.2007): 81–93. http://dx.doi.org/10.1515/jib-2007-54.
Pełny tekst źródłaYu, Limin, Xianjun Shen, Jincai Yang, Kaiping Wei, Duo Zhong i Ruilong Xiang. "Hypergraph Clustering Based on Game-Theory for Mining Microbial High-Order Interaction Module". Evolutionary Bioinformatics 16 (styczeń 2020): 117693432097057. http://dx.doi.org/10.1177/1176934320970572.
Pełny tekst źródłaAlam, M. K., Azrina Abd Aziz, S. A. Latif i Azlan Awang. "Error-Aware Data Clustering for In-Network Data Reduction in Wireless Sensor Networks". Sensors 20, nr 4 (13.02.2020): 1011. http://dx.doi.org/10.3390/s20041011.
Pełny tekst źródłaWu, Yong Liang, Bao Quan Mao, Li Xu, Dong Ming Dai i Yan Chao Liu. "The Evaluation of Module Division Programme Based on Information Entropy". Advanced Materials Research 479-481 (luty 2012): 1592–95. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.1592.
Pełny tekst źródłaRozprawy doktorskie na temat "Module clustering"
Ptitsyn, Andrey. "New algorithms for EST clustering". Thesis, University of the Western Cape, 2000. http://etd.uwc.ac.za/index.php?module=etd&.
Pełny tekst źródłaPassmoor, Sean Stuart. "Clustering studies of radio-selected galaxies". Thesis, University of the Western Cape, 2011. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_7521_1332410859.
Pełny tekst źródłaWe investigate the clustering of HI-selected galaxies in the ALFALFA survey and compare results with those obtained for HIPASS. Measurements of the angular correlation function and the inferred 3D-clustering are compared with results from direct spatial-correlation measurements. We are able to measure clustering on smaller angular scales and for galaxies with lower HI masses than was previously possible. We calculate the expected clustering of dark matter using the redshift distributions of HIPASS and ALFALFA and show that the ALFALFA sample is somewhat more anti-biased with respect to dark matter than the HIPASS sample. We are able to conform the validity of the dark matter correlation predictions by performing simulations of the non-linear structure formation. Further we examine how the bias evolves with redshift for radio galaxies detected in the the first survey.
Javar, Shima. "Measurement and comparison of clustering algorithms". Thesis, Växjö University, School of Mathematics and Systems Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-1735.
Pełny tekst źródłaIn this project, a number of different clustering algorithms are described and their workings explained. They are compared to each other by implementing them on number of graphs with a known architecture.
These clustering algorithm, in the order they are implemented, are as follows: Nearest neighbour hillclimbing, Nearest neighbour big step hillclimbing, Best neighbour hillclimbing, Best neighbour big step hillclimbing, Gem 3D, K-means simple, K-means Gem 3D, One cluster and One cluster per node.
The graphs are Unconnected, Directed KX, Directed Cycle KX and Directed Cycle.
The results of these clusterings are compared with each other according to three criteria: Time, Quality and Extremity of nodes distribution. This enables us to find out which algorithm is most suitable for which graph. These artificial graphs are then compared with the reference architecture graph to reach the conclusions.
Hu, Yang. "PV Module Performance Under Real-world Test Conditions - A Data Analytics Approach". Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1396615109.
Pełny tekst źródłaRiedl, Pavel. "Modul shlukové analýzy systému pro dolování z dat". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237095.
Pełny tekst źródłaHandfield, Louis-François. "Cis-regulatory modules clustering from sequence similarity". Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=112632.
Pełny tekst źródłaWu, Jingwen. "Model-based clustering and model selection for binned data". Thesis, Supélec, 2014. http://www.theses.fr/2014SUPL0005/document.
Pełny tekst źródłaThis thesis studies the Gaussian mixture model-based clustering approaches and the criteria of model selection for binned data clustering. Fourteen binned-EM algorithms and fourteen bin-EM-CEM algorithms are developed for fourteen parsimonious Gaussian mixture models. These new algorithms combine the advantages in computation time reduction of binning data and the advantages in parameters estimation simplification of parsimonious Gaussian mixture models. The complexities of the binned-EM and the bin-EM-CEM algorithms are calculated and compared to the complexities of the EM and the CEM algorithms respectively. In order to select the right model which fits well the data and satisfies the clustering precision requirements with a reasonable computation time, AIC, BIC, ICL, NEC, and AWE criteria, are extended to binned data clustering when the proposed binned-EM and bin-EM-CEM algorithms are used. The advantages of the different proposed methods are illustrated through experimental studies
Sampson, Joshua Neil. "Clustering genes in genetical genomics /". Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/9549.
Pełny tekst źródłaYelibi, Lionel. "Introduction to fast Super-Paramagnetic Clustering". Master's thesis, Faculty of Science, 2019. http://hdl.handle.net/11427/31332.
Pełny tekst źródłaMair, Patrick, i Marcus Hudec. "Session Clustering Using Mixtures of Proportional Hazards Models". Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2008. http://epub.wu.ac.at/598/1/document.pdf.
Pełny tekst źródłaSeries: Research Report Series / Department of Statistics and Mathematics
Książki na temat "Module clustering"
J, Davis Cecil, Herman Irving P i Turner Terry R, red. Process module metrology, control, and clustering, 11-13 September 1991, San Jose, Calif. Bellingham, Wash: SPIE--International Society for Optical Engineering, 1991.
Znajdź pełny tekst źródłaJ, Davis Cecil, Herman Irving P, Turner Terry R i Society of Photo-Optical Instrumentation Engineers., red. Process module metrology, control, and clustering: 11-13 September 1991, San Jose, California. Bellingham, Wash: SPIE, 1992.
Znajdź pełny tekst źródłaFinancial models with Levy processes and volatility clustering. Hoboken, N.J: Wiley, 2011.
Znajdź pełny tekst źródłaWilson, Caroline L. Clustering algorithms and mathematical modeling. Hauppauge, N.Y: Nova Science Publishers, 2010.
Znajdź pełny tekst źródłaRachev, S. T. Financial models with Lévy processes and volatility clustering. Hoboken, N.J: John Wiley, 2011.
Znajdź pełny tekst źródłaSergiy, Butenko, Chaovalitwongse W. Art, Pardalos P. M. 1954- i DIMACS Workshop on Clustering Problems in Biological Networks (2006 : Rutgers University), red. Clustering challenges in biological networks. New Jersry: World Scientific, 2009.
Znajdź pełny tekst źródłaSergiy, Butenko, Chaovalitwongse W. Art, Pardalos P. M. 1954- i DIMACS Workshop on Clustering Problems in Biological Networks (2006 : Rutgers University), red. Clustering challenges in biological networks. New Jersry: World Scientific, 2009.
Znajdź pełny tekst źródłaTsangarides, Charalambos G. What is fuzzy about clustering in West Africa? [Washington, D.C.]: International Monetary Fund, African Dept., 2006.
Znajdź pełny tekst źródłaE, MacCuish Norah, red. Clustering in bioinformatics and drug discovery. Boca Raton: Taylor & Francis, 2011.
Znajdź pełny tekst źródłaGrigor'ev, Anatoliy, i Evgeniy Isaev. Methods and algorithms of data processing. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1032305.
Pełny tekst źródłaCzęści książek na temat "Module clustering"
Horvath, Steve. "Clustering Procedures and Module Detection". W Weighted Network Analysis, 179–206. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8819-5_8.
Pełny tekst źródłaPaixao, Matheus, Mark Harman i Yuanyuan Zhang. "Multi-objective Module Clustering for Kate". W Search-Based Software Engineering, 282–88. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22183-0_24.
Pełny tekst źródłaYoshida, Ryo, Seiya Imoto i Tomoyuki Higuchi. "A Penalized Likelihood Estimation on Transcriptional Module-Based Clustering". W Computational Science and Its Applications – ICCSA 2005, 389–401. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11424857_42.
Pełny tekst źródłaLecca, Paola, i Angela Re. "Module Detection in Dynamic Networks by Temporal Edge Weight Clustering". W Computational Intelligence Methods for Bioinformatics and Biostatistics, 54–70. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44332-4_5.
Pełny tekst źródłada Silva Júnior, Marcondes R., i Aluizio F. R. Araújo. "Subspace Clustering Multi-module Self-organizing Maps with Two-Stage Learning". W Lecture Notes in Computer Science, 285–96. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-15937-4_24.
Pełny tekst źródłaLiang, Dong, Jun Liu, Kuanquan Wang, Gongning Luo, Wei Wang i Shuo Li. "Position-Prior Clustering-Based Self-attention Module for Knee Cartilage Segmentation". W Lecture Notes in Computer Science, 193–202. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16443-9_19.
Pełny tekst źródłade Oliveira Barros, Márcio. "Evaluating Modularization Quality as an Extra Objective in Multiobjective Software Module Clustering". W Search Based Software Engineering, 267. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23716-4_23.
Pełny tekst źródłaRay, Sumanta, Sinchani Chakraborty i Anirban Mukhopadhyay. "DCoSpect: A Novel Differentially Coexpressed Gene Module Detection Algorithm Using Spectral Clustering". W Advances in Intelligent Systems and Computing, 69–77. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2695-6_7.
Pełny tekst źródłaZamli, Kamal Z., Fakhrud Din, Nazirah Ramli i Bestoun S. Ahmed. "Software Module Clustering Based on the Fuzzy Adaptive Teaching Learning Based Optimization Algorithm". W Intelligent and Interactive Computing, 167–77. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6031-2_3.
Pełny tekst źródłaZainal, Nurul Asyikin, Kamal Z. Zamli i Fakhrud Din. "A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem". W Lecture Notes in Electrical Engineering, 219–29. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2317-5_19.
Pełny tekst źródłaStreszczenia konferencji na temat "Module clustering"
Seidel, Thomas E., i Michael R. Stark. "Learning opportunities through the use of cluster tools". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56617.
Pełny tekst źródłaLally, Kevin. "Equipment improvement methodology". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56618.
Pełny tekst źródłaSeidel, J. P., W. Wachter, William M. Triggs i Robert P. Hall. "Integrated deposition of TiN barrier layers in cluster tools". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56619.
Pełny tekst źródłaHauser, John R., i Syed A. Rizvi. "Cluster tool technology". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56620.
Pełny tekst źródłaWong, Fred, i George E. Zilberman. "Open architecture cluster tool: communication and user interface integration". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56621.
Pełny tekst źródłaBoitnott, Charles A., i David R. Craven. "Single-wafer high-pressure oxidation". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56622.
Pełny tekst źródłaHansen, Brad. "Benefits of cluster tool architecture for implementation of evolutionary equipment improvements and applications". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56623.
Pełny tekst źródłaSitte, Renate, Sima Dimitrijev i H. Barry Harrison. "Dynamic design processing of integrated circuits for an "on target" end product". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56624.
Pełny tekst źródłaGhatak, Kamakhya P. "Moss-Burstein shift in infrared materials under different physical conditions". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56625.
Pełny tekst źródłaGhatak, Kamakhya P. "Photoemission from periodic structure of graded superlattices under magnetic field". W Process Module Metrology, Control and Clustering, redaktorzy Cecil J. Davis, Irving P. Herman i Terry R. Turner. SPIE, 1992. http://dx.doi.org/10.1117/12.56626.
Pełny tekst źródłaRaporty organizacyjne na temat "Module clustering"
Oh, Man-Suk, i Adrian Raftery. Model-based Clustering with Dissimilarities: A Bayesian Approach. Fort Belvoir, VA: Defense Technical Information Center, grudzień 2003. http://dx.doi.org/10.21236/ada459759.
Pełny tekst źródłaMerl, D. Advances in Bayesian Model Based Clustering Using Particle Learning. Office of Scientific and Technical Information (OSTI), listopad 2009. http://dx.doi.org/10.2172/1010386.
Pełny tekst źródłaDe Leon, Phillip L., i Richard D. McClanahan. Efficient speaker verification using Gaussian mixture model component clustering. Office of Scientific and Technical Information (OSTI), kwiecień 2012. http://dx.doi.org/10.2172/1039402.
Pełny tekst źródłaBergman, O., i C. B. Thorn. Universality and clustering in 1 + 1 dimensional superstring-bit models. Office of Scientific and Technical Information (OSTI), marzec 1996. http://dx.doi.org/10.2172/200667.
Pełny tekst źródłaFraley, Chris, i Adrian E. Raftery. Bayesian Regularization for Normal Mixture Estimation and Model-Based Clustering. Fort Belvoir, VA: Defense Technical Information Center, sierpień 2005. http://dx.doi.org/10.21236/ada454825.
Pełny tekst źródłaFraley, Chris, Adrian Raftery i Ron Wehrensy. Incremental Model-Based Clustering for Large Datasets With Small Clusters. Fort Belvoir, VA: Defense Technical Information Center, grudzień 2003. http://dx.doi.org/10.21236/ada459790.
Pełny tekst źródłaWehrens, Ron, Lutgarde M. Buydens, Chris Fraley i Adrian E. Raftery. Model-Based Clustering for Image Segmentation and Large Datasets Via Sampling. Fort Belvoir, VA: Defense Technical Information Center, luty 2003. http://dx.doi.org/10.21236/ada459638.
Pełny tekst źródłaMurtagh, Fionn, Adrian E. Raftery i Jean-Luc Starck. Bayesian Inference for Color Image Quantization via Model-Based Clustering Trees. Fort Belvoir, VA: Defense Technical Information Center, listopad 2001. http://dx.doi.org/10.21236/ada459791.
Pełny tekst źródłaFraley, Chris, i Adrian E. Raftery. MCLUST: Software for Model-Based Clustering, Density Estimation and Discriminant Analysis. Fort Belvoir, VA: Defense Technical Information Center, październik 2002. http://dx.doi.org/10.21236/ada459792.
Pełny tekst źródłaWang, Chih-Hao, i Na Chen. Do Multi-Use-Path Accessibility and Clustering Effect Play a Role in Residents' Choice of Walking and Cycling? Mineta Transportation Institute, czerwiec 2021. http://dx.doi.org/10.31979/mti.2021.2011.
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