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Статті в журналах з теми "Monte Carlo method"
Caflisch, Russel E. "Monte Carlo and quasi-Monte Carlo methods." Acta Numerica 7 (January 1998): 1–49. http://dx.doi.org/10.1017/s0962492900002804.
Повний текст джерелаMakarova, K. V., A. G. Makarov, M. A. Padalko, V. S. Strongin, and K. V. Nefedev. "Multispin Monte Carlo Method." Dal'nevostochnyi Matematicheskii Zhurnal 20, no. 2 (November 25, 2020): 212–20. http://dx.doi.org/10.47910/femj202020.
Повний текст джерелаRajabalinejad, M. "Bayesian Monte Carlo method." Reliability Engineering & System Safety 95, no. 10 (October 2010): 1050–60. http://dx.doi.org/10.1016/j.ress.2010.04.014.
Повний текст джерелаThe Lam, Nguyen. "QUANTUM DIFFUSION MONTE CARLO METHOD FOR LOW-DIMENTIONAL SYSTEMS." Journal of Science, Natural Science 60, no. 7 (2015): 81–87. http://dx.doi.org/10.18173/2354-1059.2015-0036.
Повний текст джерелаSiyamah, Imroatus, Endah RM Putri, and Chairul Imron. "Cat bond valuation using Monte Carlo and quasi Monte Carlo method." Journal of Physics: Conference Series 1821, no. 1 (March 1, 2021): 012053. http://dx.doi.org/10.1088/1742-6596/1821/1/012053.
Повний текст джерелаKandidov, V. P. "Monte Carlo method in nonlinear statistical optics." Uspekhi Fizicheskih Nauk 166, no. 12 (1996): 1309. http://dx.doi.org/10.3367/ufnr.0166.199612c.1309.
Повний текст джерелаRashki, Mohsen. "The soft Monte Carlo method." Applied Mathematical Modelling 94 (June 2021): 558–75. http://dx.doi.org/10.1016/j.apm.2021.01.022.
Повний текст джерелаAboughantous, Charles H. "A Contributorn Monte Carlo Method." Nuclear Science and Engineering 118, no. 3 (November 1994): 160–77. http://dx.doi.org/10.13182/nse94-a19382.
Повний текст джерелаBruce, A. D., A. N. Jackson, G. J. Ackland, and N. B. Wilding. "Lattice-switch Monte Carlo method." Physical Review E 61, no. 1 (January 1, 2000): 906–19. http://dx.doi.org/10.1103/physreve.61.906.
Повний текст джерелаGubernatis, Jim, and Naomichi Hatano. "The multicanonical Monte Carlo method." Computing in Science & Engineering 2, no. 2 (March 2000): 95–102. http://dx.doi.org/10.1109/mcise.2000.5427643.
Повний текст джерелаДисертації з теми "Monte Carlo method"
Janzon, Krister. "Monte Carlo Path Simulation and the Multilevel Monte Carlo Method." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-151975.
Повний текст джерелаLacasse, Martin Daniel. "New dynamical Monte Carlo renormalization group method." Thesis, McGill University, 1990. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=60062.
Повний текст джерелаZhang, Yichuan. "Scalable geometric Markov chain Monte Carlo." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20978.
Повний текст джерелаVeld, Pieter Jacob in 't. "Monte Carlo studies of liquid structure /." Digital version:, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p9992826.
Повний текст джерелаHazelton, Martin Luke. "Method of density estimation with application to Monte Carlo methods." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334850.
Повний текст джерелаLefebvre, Geneviève 1978. "Practical issues in modern Monte Carlo integration." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103209.
Повний текст джерелаUsing an identity arising in path sampling, we then derive general expressions for the Kullback-Leibler (KL) and Jeffrey (J) divergences between two distributions with common support but from possibly different parametric families. These expressions naturally stem from path sampling when the popular geometric path is used to link the extreme densities. Expressions for the KL and J-divergences are also given for any two intermediate densities lying on the path. Estimates for the KL divergence (up to a constant) and for the J-divergence, between a posterior distribution and a selected importance density, can be obtained directly, prior to path sampling implementation. The J-divergence is shown to be helpful for choosing importance densities that minimize the error of the path sampling estimates.
Finally we present the results of a simulation study devised to investigate whether improvement in performance can be achieved by using the KL and J-divergences to select sequences of distributions in parallel (population-based) simulations, such as in the Sequential Monte Carlo Sampling and the Annealed Importance Sampling algorithms. We compare these choices of sequences to more conventional choices in the context of a mixture example. Unexpected results are obtained, and those for the KL and J-divergences are mixed. More fundamentally, we uncover the need to select the sequence of tempered distributions in accordance with the resampling scheme.
Lee, Ming Ripman, and 李明. "Monte Carlo simulation for confined electrolytes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31240513.
Повний текст джерелаLee, Ming Ripman. "Monte Carlo simulation for confined electrolytes /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22055009.
Повний текст джерелаYam, Chiu Yu. "Quasi-Monte Carlo methods for bootstrap." HKBU Institutional Repository, 2000. http://repository.hkbu.edu.hk/etd_ra/272.
Повний текст джерелаWong, Ping-yung. "Molecular clusters on surfaces : a Monte Carlo study /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20566694.
Повний текст джерелаКниги з теми "Monte Carlo method"
Lemieux, Christiane. Monte carlo and quasi-monte carlo sampling. New York: Springer, 2009.
Знайти повний текст джерелаKalos, Malvin H. Monte Carlo methods. New York: J. Wiley & Sons, 1986.
Знайти повний текст джерелаDunn, William L. Exploring Monte Carlo methods. Amsterdam: Elsevier/Academic Press, 2012.
Знайти повний текст джерела1957-, Madras Neal Noah, Fields Institute for Research in Mathematical Sciences., and Workshop on Monte Carlo Methods (1998 : Toronto, Ont.), eds. Monte Carlo methods. Providence, RI: American Mathematical Society, 2000.
Знайти повний текст джерелаI, Schueller G., ed. Monte Carlo simulation. Lisse: A.A. Balkema, 2001.
Знайти повний текст джерелаFox, Bennett L. Strategies for quasi-Monte Carlo. Boston: Kluwer Academic, 1999.
Знайти повний текст джерелаPierre, L' Ecuyer, and Owen Art B, eds. Monte Carlo and quasi-Monte Carlo methods 2008. Heidelberg: Springer, 2009.
Знайти повний текст джерелаCasella, George, and Christian P. Robert. Monte Carlo Statistical Methods. 2nd ed. New York, USA: Springer, 2004.
Знайти повний текст джерелаKroese, Dirk P., Thomas Taimre, Zdravko I. Botev, and Rueven Y. Rubinstein. Simulation and the Monte Carlo Method. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470285312.
Повний текст джерелаRubinstein, Reuven Y., and Dirk P. Kroese. Simulation and the Monte Carlo Method. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781118631980.
Повний текст джерелаЧастини книг з теми "Monte Carlo method"
Liou, William W. "Monte Carlo Method." In Encyclopedia of Microfluidics and Nanofluidics, 2315–19. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4614-5491-5_1059.
Повний текст джерелаLiou, William W. "Monte Carlo Method." In Encyclopedia of Microfluidics and Nanofluidics, 1–5. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-3-642-27758-0_1059-3.
Повний текст джерелаWeik, Martin H. "Monte Carlo method." In Computer Science and Communications Dictionary, 1045. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11803.
Повний текст джерелаMosegaard, Klaus. "Monte Carlo Method." In Encyclopedia of Mathematical Geosciences, 1–7. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-26050-7_431-2.
Повний текст джерелаMosegaard, Klaus. "Monte Carlo Method." In Encyclopedia of Mathematical Geosciences, 1–7. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_431-1.
Повний текст джерелаMosegaard, Klaus. "Monte Carlo Method." In Encyclopedia of Mathematical Geosciences, 890–96. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_431.
Повний текст джерелаChoe, Geon Ho. "The Monte Carlo Method for Option Pricing Monte Carlo method." In Universitext, 501–17. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25589-7_28.
Повний текст джерелаBuckley, James J., and Leonard J. Jowers. "Fuzzy Monte Carlo Method." In Monte Carlo Methods in Fuzzy Optimization, 57–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-76290-4_6.
Повний текст джерелаRollett, Anthony D., and Priya Manohar. "The Monte Carlo Method." In Continuum Scale Simulation of Engineering Materials, 77–114. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2005. http://dx.doi.org/10.1002/3527603786.ch4.
Повний текст джерелаTildesley, D. J. "The Monte Carlo Method." In Computer Simulation in Chemical Physics, 1–22. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1679-4_1.
Повний текст джерелаТези доповідей конференцій з теми "Monte Carlo method"
Wilding, Nigel B. "Phase Switch Monte Carlo." In THE MONTE CARLO METHOD IN THE PHYSICAL SCIENCES: Celebrating the 50th Anniversary of the Metropolis Algorithm. AIP, 2003. http://dx.doi.org/10.1063/1.1632147.
Повний текст джерелаFrenkel, D. "Biased Monte Carlo Methods." In THE MONTE CARLO METHOD IN THE PHYSICAL SCIENCES: Celebrating the 50th Anniversary of the Metropolis Algorithm. AIP, 2003. http://dx.doi.org/10.1063/1.1632121.
Повний текст джерелаBilgin, Muhammed, and Tolga Ensari. "Robot localization with Monte Carlo method." In 2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT). IEEE, 2017. http://dx.doi.org/10.1109/ebbt.2017.7956755.
Повний текст джерелаLing*, Yue, Huazhong Wang, and Shaoyong Liu. "Monte Carlo background velocity inversion method." In Beijing 2014 International Geophysical Conference & Exposition, Beijing, China, 21-24 April 2014. Society of Exploration Geophysicists and Chinese Petroleum Society, 2014. http://dx.doi.org/10.1190/igcbeijing2014-188.
Повний текст джерелаPapp, Zsolt, Janos Kornis, and Balazs Gombkoto. "Monte Carlo method in digital holography." In Speckle Metrology 2003. SPIE, 2003. http://dx.doi.org/10.1117/12.516573.
Повний текст джерелаGonzalez-Jorge, H., J. L. Valencia, V. Alvarez, F. Rodriguez, and F. J. Yebra. "Monte-Carlo method in AFM calibration." In 2009 Spanish Conference on Electron Devices (CDE). IEEE, 2009. http://dx.doi.org/10.1109/sced.2009.4800526.
Повний текст джерелаStoffova, Veronika, and R. Horváth. "MONTE CARLO METHOD IN EDUCATIONAL PRACTICE." In 13th annual International Conference of Education, Research and Innovation. IATED, 2020. http://dx.doi.org/10.21125/iceri.2020.1532.
Повний текст джерелаZhu, Juan, Shuai Wang, Da-wei Wang, Yan-ying Liu, and Yan-jie Wang. "Monte Carlo Tracking Method with Threshold Constraint." In 2009 2nd International Congress on Image and Signal Processing (CISP). IEEE, 2009. http://dx.doi.org/10.1109/cisp.2009.5301685.
Повний текст джерелаChen, Nanguang. "Controlled Monte Carlo Method for Reflection Geometry." In Biomedical Topical Meeting. Washington, D.C.: OSA, 2006. http://dx.doi.org/10.1364/bio.2006.me9.
Повний текст джерелаDIMOV, IVAN, and ANETA KARAIVANOVA. "A POWER METHOD WITH MONTE CARLO ITERATIONS." In Proceedings of the Fourth International Conference. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814291071_0022.
Повний текст джерелаЗвіти організацій з теми "Monte Carlo method"
Hill, James Lloyd. Introduction to the Monte Carlo Method. Office of Scientific and Technical Information (OSTI), June 2020. http://dx.doi.org/10.2172/1634920.
Повний текст джерелаBlomquist, R. N., and E. M. Gelbard. Alternative implementations of the Monte Carlo power method. Office of Scientific and Technical Information (OSTI), March 2002. http://dx.doi.org/10.2172/793906.
Повний текст джерелаSvatos, M. The macro response Monte Carlo method for electron transport. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/3847.
Повний текст джерелаFishman, George S. Sensitivity Analysis Using the Monte Carlo Acceptance-Rejection Method. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada201261.
Повний текст джерелаCarlin, Bradley P., and Alan E. Gelfand. An Iterative Monte Carlo Method for Nonconjugate Bayesian Analysis. Fort Belvoir, VA: Defense Technical Information Center, September 1992. http://dx.doi.org/10.21236/ada255991.
Повний текст джерелаTaro Ueki. A Multivariate Time Series Method for Monte Carlo Reactor Analysis. Office of Scientific and Technical Information (OSTI), August 2008. http://dx.doi.org/10.2172/935876.
Повний текст джерелаRichie, David A., James A. Ross, Song J. Park, and Dale R. Shires. A Monte Carlo Method for Multi-Objective Correlated Geometric Optimization. Fort Belvoir, VA: Defense Technical Information Center, May 2014. http://dx.doi.org/10.21236/ada603830.
Повний текст джерелаActon, Scott T., and Bing Li. A Sequential Monte Carlo Method for Real-time Tracking of Multiple Targets. Fort Belvoir, VA: Defense Technical Information Center, May 2010. http://dx.doi.org/10.21236/ada532576.
Повний текст джерелаBoyd, Iain D. A Threshold Line Dissociation Model for the Direct Simulation Monte Carlo Method,. Fort Belvoir, VA: Defense Technical Information Center, May 1996. http://dx.doi.org/10.21236/ada324950.
Повний текст джерелаPolitis, Dimitris N., Raffaella Giacomini, and Halbert White. A warp-speed method for conducting Monte Carlo experiments involving bootstrap estimators. Cemmap, May 2012. http://dx.doi.org/10.1920/wp.cem.2012.1112.
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