Littérature scientifique sur le sujet « Global Optimization, Clustering Methods »
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Articles de revues sur le sujet "Global Optimization, Clustering Methods"
Törn, A. A. « Clustering Methods in Global Optimization ». IFAC Proceedings Volumes 19, no 5 (mai 1986) : 247–52. http://dx.doi.org/10.1016/s1474-6670(17)59803-1.
Texte intégralRinnooy Kan, A. H. G., et G. T. Timmer. « Stochastic global optimization methods part I : Clustering methods ». Mathematical Programming 39, no 1 (septembre 1987) : 27–56. http://dx.doi.org/10.1007/bf02592070.
Texte intégralBagattini, Francesco, Fabio Schoen et Luca Tigli. « Clustering methods for large scale geometrical global optimization ». Optimization Methods and Software 34, no 5 (1 mars 2019) : 1099–122. http://dx.doi.org/10.1080/10556788.2019.1582651.
Texte intégralSchoen, Fabio, et Luca Tigli. « Efficient large scale global optimization through clustering-based population methods ». Computers & ; Operations Research 127 (mars 2021) : 105165. http://dx.doi.org/10.1016/j.cor.2020.105165.
Texte intégralAldosari, Fahd, Laith Abualigah et Khaled H. Almotairi. « A Normal Distributed Dwarf Mongoose Optimization Algorithm for Global Optimization and Data Clustering Applications ». Symmetry 14, no 5 (17 mai 2022) : 1021. http://dx.doi.org/10.3390/sym14051021.
Texte intégralFong, Simon, Suash Deb, Xin-She Yang et Yan Zhuang. « Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms ». Scientific World Journal 2014 (2014) : 1–16. http://dx.doi.org/10.1155/2014/564829.
Texte intégralGerasina, O., V. Korniienko, O. Gusev, K. Sosnin et S. Matsiuk. « Detecting fishing URLs using fuzzy clustering algorithms with global optimization ». System technologies 2, no 139 (30 mars 2022) : 53–67. http://dx.doi.org/10.34185/1562-9945-2-139-2022-06.
Texte intégralDuan, Yiqiang, Haoliang Yuan, Chun Sing Lai et Loi Lei Lai. « Fusing Local and Global Information for One-Step Multi-View Subspace Clustering ». Applied Sciences 12, no 10 (18 mai 2022) : 5094. http://dx.doi.org/10.3390/app12105094.
Texte intégralWen, Guoqiu, Yonghua Zhu, Linjun Chen, Mengmeng Zhan et Yangcai Xie. « Global and Local Structure Preservation for Nonlinear High-dimensional Spectral Clustering ». Computer Journal 64, no 7 (14 mai 2021) : 993–1004. http://dx.doi.org/10.1093/comjnl/bxab020.
Texte intégralWang, Hong Chun, Feng Wen Wen et Feng Song. « Clustering Algorithm Based on Improved Particle Swarm Optimization ». Advanced Materials Research 765-767 (septembre 2013) : 486–88. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.486.
Texte intégralThèses sur le sujet "Global Optimization, Clustering Methods"
SOUZA, Ellen Polliana Ramos. « Swarm optimization clustering methods for opinion mining ». Universidade Federal de Pernambuco, 2017. https://repositorio.ufpe.br/handle/123456789/25227.
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Opinion Mining (OM), also known as sentiment analysis, is the field of study that analyzes people’s sentiments, evaluations, attitudes, and emotions about different entities expressed in textual input. This is accomplished through the classification of an opinion into categories, such as positive, negative, or neutral. Supervised machine learning (ML) and lexicon-based are the most frequent approaches for OM. However, these approaches require considerable effort for preparing training data and to build the opinion lexicon, respectively. In order to address the drawbacks of these approaches, this Thesis proposes the use of unsupervised clustering approach for the OM task which is able to produce accurate results for several domains without manually labeled data for the training step or tools which are language dependent. Three swarm algorithms based on Particle Swarm Optimization (PSO) and Cuckoo Search (CS) are proposed: the DPSOMUT which is based on a discrete PSO binary version, the IDPSOMUT that is based on an Improved Self-Adaptive PSO algorithm with detection function, and the IDPSOMUT/CS that is a hybrid version of IDPSOMUT and CS. Several experiments were conducted with different corpora types, domains, text language, class balancing, fitness function, and pre-processing techniques. The effectiveness of the clustering algorithms was evaluated with external measures such as accuracy, precision, recall, and F-score. From the statistical analysis, it was possible to observe that the swarm-based algorithms, especially the PSO ones, were able to find better solutions than conventional grouping techniques, such as K-means and Agglomerative. The PSO-based algorithms achieved better accuracy using a word bigram pre-processing and the Global Silhouette as fitness function. The OBCC corpus is also another contribution of this Thesis and contains a gold collection with 2,940 tweets in Brazilian Portuguese with opinions of consumers about products and services.
A mineração de opinião, também conhecida como análise de sentimento, é um campo de estudo que analisa os sentimentos, opiniões, atitudes e emoções das pessoas sobre diferentes entidades, expressos de forma textual. Tal análise é obtida através da classificação das opiniões em categorias, tais como positiva, negativa ou neutra. As abordagens de aprendizado supervisionado e baseadas em léxico são mais comumente utilizadas na mineração de opinião. No entanto, tais abordagens requerem um esforço considerável para preparação da base de dados de treinamento e para construção dos léxicos de opinião, respectivamente. A fim de minimizar as desvantagens das abordagens apresentadas, esta Tese propõe o uso de uma abordagem de agrupamento não supervisionada para a tarefa de mineração de opinião, a qual é capaz de produzir resultados precisos para diversos domínios sem a necessidade de dados rotulados manualmente para a etapa treinamento e sem fazer uso de ferramentas dependentes de língua. Três algoritmos de agrupamento não-supervisionado baseados em otimização de partícula de enxame (Particle Swarm Optimization - PSO) são propostos: o DPSOMUT, que é baseado em versão discreta do PSO; o IDPSOMUT, que é baseado em uma versão melhorada e autoadaptativa do PSO com função de detecção; e o IDPSOMUT/CS, que é uma versão híbrida do IDPSOMUT com o Cuckoo Search (CS). Diversos experimentos foram conduzidos com diferentes tipos de corpora, domínios, idioma do texto, balanceamento de classes, função de otimização e técnicas de pré-processamento. A eficácia dos algoritmos de agrupamento foi avaliada com medidas externas como acurácia, precisão, revocação e f-medida. A partir das análises estatísticas, os algortimos baseados em inteligência coletiva, especialmente os baseado em PSO, obtiveram melhores resultados que os algortimos que utilizam técnicas convencionais de agrupamento como o K-means e o Agglomerative. Os algoritmos propostos obtiveram um melhor desempenho utilizando o pré-processamento baseado em n-grama e utilizando a Global Silhouete como função de otimização. O corpus OBCC é também uma contribuição desta Tese e contem uma coleção dourada com 2.940 tweets com opiniões de consumidores sobre produtos e serviços em Português brasileiro.
Ren, Zhiwei. « Portfolio Construction using Clustering Methods ». Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-042605-092010/.
Texte intégralSchütze, Oliver. « Set oriented methods for global optimization ». [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=976566982.
Texte intégralGutmann, H. M. « Radial basis function methods for global optimization ». Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.599804.
Texte intégralStepanenko, Svetlana. « Global Optimization Methods based on Tabu Search ». Doctoral thesis, kostenfrei, 2008. http://www.opus-bayern.de/uni-wuerzburg/volltexte/2008/3060/.
Texte intégralPettersson, Tobias. « Global optimization methods for estimation of descriptive models ». Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11781.
Texte intégralUsing mathematical models with the purpose to understand and store knowlegde about a system is not a new field in science with early contributions dated back to, e.g., Kepler’s laws of planetary motion.
The aim is to obtain such a comprehensive predictive and quantitative knowledge about a phenomenon so that mathematical expressions or models can be used to forecast every relevant detail about that phenomenon. Such models can be used for reducing pollutions from car engines; prevent aviation incidents; or developing new therapeutic drugs. Models used to forecast, or predict, the behavior of a system are refered to predictive models. For such, the estimation problem aims to find one model and is well known and can be handeled by using standard methods for global nonlinear optimization.
Descriptive models are used to obtain and store quantitative knowledge of system. Estimation of descriptive models has not been much described by the literature so far; instead the methods used for predictive models have beed applied. Rather than finding one particular model, the parameter estimation for descriptive models aims to find every model that contains descriptive information about the system. Thus, the parameter estimation problem for descriptive models can not be stated as a standard optimization problem.
The main objective for this thesis is to propose methods for estimation of descriptive models. This is made by using methods for nonlinear optimization including both new and existing theory.
McMeen, John Norman Jr. « Ranking Methods for Global Optimization of Molecular Structures ». Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etd/2447.
Texte intégralAkteke, Basak. « Derivative Free Optimization Methods : Application In Stirrer Configuration And Data Clustering ». Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606591/index.pdf.
Texte intégrals design variables is not directly available. This nonlinear objective function is obtained from the flow field by the flow solver. We present and interpret numerical results of this implementation. Moreover, a contribution is given to a survey and a distinction of DFO research directions, to an analysis and discussion of these. We also state a derivative free algorithm used within a clustering algorithm in combination with non-smooth optimization techniques to reveal the effectiveness of derivative free methods in computations. This algorithm is applied on some data sets from various sources of public life and medicine. We compare various methods, their practical backgrounds, and conclude with a summary and outlook. This work may serve as a preparation of possible future research.
Stolpe, Mathias. « On Models and Methods for Global Optimization of Structural Topology ». Doctoral thesis, KTH, Mathematics, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3478.
Texte intégralThis thesis consists of an introduction and sevenindependent, but closely related, papers which all deal withproblems in structural optimization. In particular, we considermodels and methods for global optimization of problems intopology design of discrete and continuum structures.
In the first four papers of the thesis the nonconvex problemof minimizing the weight of a truss structure subject to stressconstraints is considered. First itis shown that a certainsubclass of these problems can equivalently be cast as linearprograms and thus efficiently solved to global optimality.Thereafter, the behavior of a certain well-known perturbationtechnique is studied. It is concluded that, in practice, thistechnique can not guarantee that a global minimizer is found.Finally, a convergent continuous branch-and-bound method forglobal optimization of minimum weight problems with stress,displacement, and local buckling constraints is developed.Using this method, several problems taken from the literatureare solved with a proof of global optimality for the firsttime.
The last three papers of the thesis deal with topologyoptimization of discretized continuum structures. Theseproblems are usually modeled as mixed or pure nonlinear 0-1programs. First, the behavior of certain often usedpenalization methods for minimum compliance problems isstudied. It is concluded that these methods may fail to producea zero-one solution to the considered problem. To remedy this,a material interpolation scheme based on a rational functionsuch that compli- ance becomes a concave function is proposed.Finally, it is shown that a broad range of nonlinear 0-1topology optimization problems, including stress- anddisplacement-constrained minimum weight problems, canequivalently be modeled as linear mixed 0-1 programs. Thisresult implies that any of the standard methods available forgeneral linear integer programming can now be used on topologyoptimization problems.
Keywords:topology optimization, global optimization,stress constraints, linear programming, mixed integerprogramming, branch-and-bound.
Robertson, Blair Lennon. « Direct Search Methods for Nonsmooth Problems using Global Optimization Techniques ». Thesis, University of Canterbury. Mathematics and Statistics, 2010. http://hdl.handle.net/10092/5060.
Texte intégralLivres sur le sujet "Global Optimization, Clustering Methods"
M, Pardalos Panos, et Rosen J. B, dir. Computational methods in global optimization. Basel : J.C. Baltzer, 1990.
Trouver le texte intégral1948-, Stoffa Paul L., dir. Global optimization methods in geophysical inversion. Amsterdam : Elsevier, 1995.
Trouver le texte intégral1941-, Rokne J., dir. New computer methods for global optimization. Chichester, West Sussex, England : Horwood, 1988.
Trouver le texte intégralFloudas, Christodoulos A. Deterministic global optimization : Theory, methods, and applications. Dordrecht : Kluwer Academic Publishers, 2000.
Trouver le texte intégralFloudas, Christodoulos A. Deterministic Global Optimization : Theory, Methods and Applications. Boston, MA : Springer US, 2000.
Trouver le texte intégralBruhn, Andrés, Thomas Pock et Xue-Cheng Tai, dir. Efficient Algorithms for Global Optimization Methods in Computer Vision. Berlin, Heidelberg : Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54774-4.
Texte intégralGlobal methods in optimal control theory. New York : M. Dekker, 1996.
Trouver le texte intégralAkulenko, Leonid D. Problems and Methods of Optimal Control. Dordrecht : Springer Netherlands, 1994.
Trouver le texte intégralA, Floudas Christodoulos, et Pardalos P. M. 1954-, dir. State of the art in global optimization : Computational methods and applications. Dordrecht : Kluwer Academic Publishers, 1996.
Trouver le texte intégralBobylev, N. A. Geometrical Methods in Variational Problems. Dordrecht : Springer Netherlands, 1999.
Trouver le texte intégralChapitres de livres sur le sujet "Global Optimization, Clustering Methods"
Liu, Kai, Duane Detwiler et Andres Tovar. « Metamodel-Based Global Optimization of Vehicle Structures for Crashworthiness Supported by Clustering Methods ». Dans Advances in Structural and Multidisciplinary Optimization, 1545–57. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67988-4_116.
Texte intégralHorst, Reiner, et Hoang Tuy. « Cutting Methods ». Dans Global Optimization, 175–218. Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-662-02598-7_5.
Texte intégralHorst, Reiner, et Hoang Tuy. « Cutting Methods ». Dans Global Optimization, 175–218. Berlin, Heidelberg : Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02947-3_5.
Texte intégralHorst, Reiner, et Hoang Tuy. « Cutting Methods ». Dans Global Optimization, 181–224. Berlin, Heidelberg : Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03199-5_5.
Texte intégralHorst, Reiner, et Hoang Tuy. « Successive Approximation Methods ». Dans Global Optimization, 219–85. Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-662-02598-7_6.
Texte intégralHorst, Reiner, et Hoang Tuy. « Successive Partition Methods ». Dans Global Optimization, 286–370. Berlin, Heidelberg : Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-662-02598-7_7.
Texte intégralHorst, Reiner, et Hoang Tuy. « Successive Approximation Methods ». Dans Global Optimization, 219–85. Berlin, Heidelberg : Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02947-3_6.
Texte intégralHorst, Reiner, et Hoang Tuy. « Successive Partition Methods ». Dans Global Optimization, 286–370. Berlin, Heidelberg : Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02947-3_7.
Texte intégralHorst, Reiner, et Hoang Tuy. « Successive Approximation Methods ». Dans Global Optimization, 225–93. Berlin, Heidelberg : Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03199-5_6.
Texte intégralHorst, Reiner, et Hoang Tuy. « Successive Partition Methods ». Dans Global Optimization, 295–380. Berlin, Heidelberg : Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03199-5_7.
Texte intégralActes de conférences sur le sujet "Global Optimization, Clustering Methods"
Bifulco, Ida, et Stefano Cirillo. « Discovery Multiple Data Structures in Big Data through Global Optimization and Clustering Methods ». Dans 2018 22nd International Conference Information Visualisation (IV). IEEE, 2018. http://dx.doi.org/10.1109/iv.2018.00030.
Texte intégralXiaosong, GUO, Teng Long, Di Wu, Zhu Wang et Li Liu. « RBF Metamodel Assisted Global Optimization Method Using Particle Swarm Evolution and Fuzzy Clustering for Sequential Sampling ». Dans 15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia : American Institute of Aeronautics and Astronautics, 2014. http://dx.doi.org/10.2514/6.2014-2305.
Texte intégralLiu, Kai, Andrés Tovar, Emily Nutwell et Duane Detwiler. « Towards Nonlinear Multimaterial Topology Optimization Using Unsupervised Machine Learning and Metamodel-Based Optimization ». Dans ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46534.
Texte intégralHoeltzel, D. A., et W. H. Chieng. « Statistical Machine Learning for the Cognitive Selection of Nonlinear Programming Algorithms in Engineering Design Optimization ». Dans ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0009.
Texte intégralGimbutienė, Gražina, et Antanas Žilinskas. « Clustering-based statistical global optimization ». Dans NUMERICAL COMPUTATIONS : THEORY AND ALGORITHMS (NUMTA–2016) : Proceedings of the 2nd International Conference “Numerical Computations : Theory and Algorithms”. Author(s), 2016. http://dx.doi.org/10.1063/1.4965342.
Texte intégralHaas, Kyle. « Prediction of Structural Reliability Through an Alternative Variability-Based Methodology ». Dans ASME 2019 Verification and Validation Symposium. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/vvs2019-5150.
Texte intégralBifulco, Ida, Carmine Fedullo, Francesco Napolitano, Giancarlo Raiconi et Roberto Tagliaferri. « Global optimization, Meta Clustering and consensus clustering for class prediction ». Dans 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178789.
Texte intégralJohnson, Ryan K., et Ferat Sahin. « Particle swarm optimization methods for data clustering ». Dans 2009 Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control (ICSCCW). IEEE, 2009. http://dx.doi.org/10.1109/icsccw.2009.5379452.
Texte intégralL. Stoffa, P., M. K. Sen, C. Varela et R. K. Chunduru. « Geophysical applications of global optimization methods ». Dans 56th EAEG Meeting. European Association of Geoscientists & Engineers, 1994. http://dx.doi.org/10.3997/2214-4609.201410084.
Texte intégralSen, M. K., P. L. Stoffa et R. K. Chunduru. « Geophysical Application of Global Optimization Methods ». Dans 3rd International Congress of the Brazilian Geophysical Society. European Association of Geoscientists & Engineers, 1993. http://dx.doi.org/10.3997/2214-4609-pdb.324.91.
Texte intégralRapports d'organisations sur le sujet "Global Optimization, Clustering Methods"
Dunlavy, Daniel M., et Dianne P. O'Leary. Homotopy optimization methods for global optimization. Office of Scientific and Technical Information (OSTI), décembre 2005. http://dx.doi.org/10.2172/876373.
Texte intégralGlover, Fred. Probabilistic Methods for Global Optimization in Continuous Variables. Fort Belvoir, VA : Defense Technical Information Center, novembre 1995. http://dx.doi.org/10.21236/ada304297.
Texte intégralGlover, Fred. Probabilistic Methods or Global Optimization in Continuous Variables. Fort Belvoir, VA : Defense Technical Information Center, novembre 1995. http://dx.doi.org/10.21236/ada311405.
Texte intégralDennis, John E., Shou-Bai B. Li et Richard A. Tapia. A Unified Approach to Global Convergence of Trust-Region Methods for Nonsmooth Optimization. Fort Belvoir, VA : Defense Technical Information Center, juillet 1993. http://dx.doi.org/10.21236/ada455260.
Texte intégralEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak et Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, juillet 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Texte intégralMcElwain, Terry, Eugene Pipano, Guy Palmer, Varda Shkap, Stephen Hines et Douglas Jasmer. Protection of Cattle Against Babesiosis : Immunization with Recombinant DNA Derived Apical Complex Antigens of Babesia bovis. United States Department of Agriculture, juin 1995. http://dx.doi.org/10.32747/1995.7612835.bard.
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