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Relevant bibliographies by topics / Numerical / Journal articles

Journal articles on the topic 'Numerical'

To see the other types of publications on this topic, follow the link: Numerical.

Author: Grafiati

Published: 4 June 2021

Last updated: 1 June 2024

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1

Tsujimoto, Koichi, Toshihiko Shakouchi, Shuji Sasazaki, and Toshitake Ando. "Direct Numerical Simulation of Jet Mixing Control Using Combined Jets(Numerical Simulation)." Proceedings of the International Conference on Jets, Wakes and Separated Flows (ICJWSF) 2005 (2005): 725–30. http://dx.doi.org/10.1299/jsmeicjwsf.2005.725.

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2

Lima Júnior, Édio Pereira, Wendel Rodrigues Miranda, André Luiz Tenório Rezende, and Arnaldo Ferreira. "Numerical Simulation of Impact." International Journal of Innovative Research in Engineering & Management 5, no. 1 (January 2018): 24–29. http://dx.doi.org/10.21276/ijirem.2018.5.1.6.

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3

Umrzoqova, Kommuna Xursanovna. "Numerical Technologies In Economy." American Journal of Interdisciplinary Innovations and Research 03, no. 05 (May 7, 2021): 100–104. http://dx.doi.org/10.37547/tajiir/volume03issue05-18.

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This article deals with the several key technologies of the numerical economy, such as BIMPLM,loT, SRM, BIG DATA.. Analyzed the advantages and the risks of the implementation of numerical technologies in economy and the role of numerical technologies in the development of economy.

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4

Tabsum, B. "Python for Numerical Integration." International Journal of Science and Research (IJSR) 12, no. 5 (May 5, 2023): 1801–5. http://dx.doi.org/10.21275/mr23521182224.

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5

Ward, Jennifer A. "Catalogo Numerico Ricordi (Ricordi Online Numerical Catalogue)." Music Reference Services Quarterly 18, no. 2 (April 3, 2015): 115–19. http://dx.doi.org/10.1080/10588167.2015.1029810.

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6

Akat, M., R. Kosker, and A. Sirma. "On the numerical schemes for Langevin-type equations." BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS 99, no. 3 (September 30, 2020): 62–74. http://dx.doi.org/10.31489/2020m3/62-74.

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In this paper, a numerical approach is proposed based on the variation-of-constants formula for the numerical discretization Langevin-type equations. Linear and non-linear cases are treated separately. The proofs of convergence have been provided for the linear case, and the numerical implementation has been executed for the non-linear case. The order one convergence for the numerical scheme has been shown both theoretically and numerically. The stability of the numerical scheme has been shown numerically and depicted graphically.

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7

Denis, Christophe, and Sethy Montan. "Numerical Verification of Industrial Numerical Codes." ESAIM: Proceedings 35 (March 2012): 107–13. http://dx.doi.org/10.1051/proc/201235006.

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8

Li, Chi-Kwong. "C-numerical ranges andC-numerical radii." Linear and Multilinear Algebra 37, no. 1-3 (June 1994): 51–82. http://dx.doi.org/10.1080/03081089408818312.

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9

D’Anna, M., and F. Strazzanti. "The numerical duplication of a numerical semigroup." Semigroup Forum 87, no. 1 (December 4, 2012): 149–60. http://dx.doi.org/10.1007/s00233-012-9451-x.

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10

OKAWA, HIROTADA. "INITIAL CONDITIONS FOR NUMERICAL RELATIVITY: INTRODUCTION TO NUMERICAL METHODS FOR SOLVING ELLIPTIC PDEs." International Journal of Modern Physics A 28, no. 22n23 (September 20, 2013): 1340016. http://dx.doi.org/10.1142/s0217751x13400162.

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Numerical relativity became a powerful tool to investigate the dynamics of binary problems with black holes or neutron stars as well as the very structure of General Relativity. Although public numerical relativity codes are available to evolve such systems, a proper understanding of the methods involved is quite important. Here, we focus on the numerical solution of elliptic partial differential equations. Such equations arise when preparing initial data for numerical relativity, but also for monitoring the evolution of black holes. Because such elliptic equations play an important role in many branches of physics, we give an overview of the topic, and show how to numerically solve them with simple examples and sample codes written in C ++ and Fortran90 for beginners in numerical relativity or other fields requiring numerical expertise.

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11

Matušů, Josef, Gejza Dohnal, and Martin Matušů. "On one method of numerical integration." Applications of Mathematics 36, no. 4 (1991): 241–63. http://dx.doi.org/10.21136/am.1991.104464.

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12

Botta, Nicola, and Rolf Jeltsch. "A numerical method for unsteady flows." Applications of Mathematics 40, no. 3 (1995): 175–201. http://dx.doi.org/10.21136/am.1995.134290.

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13

H, Girija Bai. "Numerical Analysis of Aneurysm in Artery." International Journal of Psychosocial Rehabilitation 24, no. 4 (February 28, 2020): 4975–81. http://dx.doi.org/10.37200/ijpr/v24i4/pr201597.

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14

ROTARU, Constantin. "NUMERICAL SOLUTIONS FOR COMBUSTION WAVE VELOCITY." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 21, no. 1 (October 8, 2019): 184–93. http://dx.doi.org/10.19062/2247-3173.2019.21.25.

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15

Song, Daegene. "Numerical Analysis in Entanglement Swapping Protocols." NeuroQuantology 20, no. 2 (April 1, 2022): 153–57. http://dx.doi.org/10.14704/nq.2022.20.2.nq22083.

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Entanglement has recently been one of the most essential elements in the development of various quantum technologies. In fact, a swapping protocol was introduced to create a long-distance entanglement from multiple shorter ones. Extending the previous work, this paper provides a more detailed numerical analysis to help create long-distance entanglement out of the two non-maximal three-level states. Specifically, it shows that while the protocol does not always yield optimal results, namely, the weaker link, there is a substantial number of states that yield an optimal result. Moreover, we discuss the numerical approach in showing the existence of states that provide a result close to the optimal outcome, which may be useful in realizing the long-distance entanglement used in quantum technology.

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16

BRUZZO, UGO, and BEATRIZ GRAÑA OTERO. "NUMERICALLY FLAT HIGGS VECTOR BUNDLES." Communications in Contemporary Mathematics 09, no. 04 (August 2007): 437–46. http://dx.doi.org/10.1142/s0219199707002526.

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After providing a suitable definition of numerical effectiveness for Higgs bundles, and a related notion of numerical flatness, in this paper we prove, together with some side results, that all Chern classes of a Higgs-numerically flat Higgs bundle vanish, and that a Higgs bundle is Higgs-numerically flat if and only if it is has a filtration whose quotients are flat stable Higgs bundles. We also study the relation between these numerical properties of Higgs bundles and (semi)stability.

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17

Bourgeron, Patrick, Pierre Legendre, and Louis Legendre. "Numerical Ecology." Arctic, Antarctic, and Alpine Research 32, no. 2 (May 2000): 218. http://dx.doi.org/10.2307/1552458.

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18

Buxton, William. "Numerical Controversy." Computer Music Journal 12, no. 3 (1988): 8. http://dx.doi.org/10.2307/3680331.

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19

Ellerby, F. B., I. Jacques, and C. Judd. "Numerical Analysis." Mathematical Gazette 72, no. 460 (June 1988): 156. http://dx.doi.org/10.2307/3618958.

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20

Jackson, I. R. H., and Bill Dalton. "Numerical Analysis." Mathematical Gazette 76, no. 476 (July 1992): 307. http://dx.doi.org/10.2307/3619167.

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21

Mudge, Michael Richard, and Peter R. Turner. "Numerical Analysis." Mathematical Gazette 81, no. 491 (July 1997): 342. http://dx.doi.org/10.2307/3619249.

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22

Iserles, A., G. Hammerlin, and K. H. Hoffmann. "Numerical Mathematics." Mathematical Gazette 78, no. 481 (March 1994): 91. http://dx.doi.org/10.2307/3619466.

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23

G., W., Gunther Hammerlin, Karl-Heinz Hoffmann, and Larry Schumaker. "Numerical Mathematics." Mathematics of Computation 58, no. 198 (April 1992): 855. http://dx.doi.org/10.2307/2153223.

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24

Chen, Justin, and Joe Kileel. "Numerical implicitization." Journal of Software for Algebra and Geometry 9, no. 1 (July 5, 2019): 55–63. http://dx.doi.org/10.2140/jsag.2019.9.55.

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25

Siegler, Robert S., and David W. Braithwaite. "Numerical Development." Annual Review of Psychology 68, no. 1 (January 3, 2017): 187–213. http://dx.doi.org/10.1146/annurev-psych-010416-044101.

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26

Strawderman, William E., and Rainer Kress. "Numerical Analysis." Journal of the American Statistical Association 95, no. 449 (March 2000): 348. http://dx.doi.org/10.2307/2669585.

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27

Murakami, Akira, Akihiko Wakai, and Kazunori Fujisawa. "Numerical Methods." Soils and Foundations 50, no. 6 (December 2010): 877–92. http://dx.doi.org/10.3208/sandf.50.877.

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28

Keppens, R. "Numerical Magnetohydrodynamics." Fusion Science and Technology 53, no. 2T (February 2008): 135–43. http://dx.doi.org/10.13182/fst08-a1699.

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29

Seidel, Edward, and Wai-Mo Suen. "NUMERICAL RELATIVITY." International Journal of Modern Physics C 05, no. 02 (April 1994): 181–87. http://dx.doi.org/10.1142/s012918319400012x.

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The present status of numerical relativity is reviewed. There are five closely interconnected aspects of numerical relativity: (1) Formulation. The general covariant Einstein equations are reformulated in a way suitable for numerical study by separating the 4-dimensional spacetime into a 3-dimensional space evolving in time. (2) Techniques. A set of tools is developed for determining gauge choices, setting boundary and initial conditions, handling spacetime singularities, etc. As required by the special physical and mathematical properties of general relativity, such techniques are indispensable for the numerical evolutions of spacetime. (3) Coding. The optimal use of parallel processing is crucial for many problems in numerical relativity, due to the intrinsic complexity of the theory. (4) Visualization. Numerical relativity is about the evolutions of 3-dimensional geometric structures. There are special demands on visualization. (5) Interpretation and Understanding. The integration of numerical data in relativity into a consistent physical picture is complicated by gauge and coordinate degrees of freedoms and other difficulties. We give a brief overview of the progress made in these areas.

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30

Gray, Jeremy. "Numerical concoctions." Nature 402, no. 6763 (December 1999): 724–25. http://dx.doi.org/10.1038/45378.

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31

Dubois, Paul F., Konrad Hinsen, and James Hugunin. "Numerical Python." Computers in Physics 10, no. 3 (1996): 262. http://dx.doi.org/10.1063/1.4822400.

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32

Burton, Ann. "Numerical value." Practical Pre-School 2007, no. 72 (January 2007): 5–6. http://dx.doi.org/10.12968/prps.2007.1.72.38615.

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33

Baker, Joanne. "Numerical reading." Nature 460, no. 7259 (August 2009): 1083. http://dx.doi.org/10.1038/4601083b.

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34

Price, Thomas McMurray. "Numerical cohomology." Algebraic Geometry 4, no. 2 (March 15, 2017): 136–59. http://dx.doi.org/10.14231/ag-2017-007.

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35

Tribbey, Will. "Numerical Recipes." ACM SIGSOFT Software Engineering Notes 35, no. 6 (November 27, 2010): 30–31. http://dx.doi.org/10.1145/1874391.187410.

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36

Hull, T. E., A. Abrham, M. S. Cohen, A. F. X., C. B. Hall, D. A. Penny, and J. T. M. "Numerical Turing." ACM SIGNUM Newsletter 20, no. 3 (July 1985): 26–34. http://dx.doi.org/10.1145/1057947.1057949.

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37

Pile, David. "Numerical solution." Nature Photonics 9, no. 1 (December 23, 2014): 5–6. http://dx.doi.org/10.1038/nphoton.2014.305.

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38

Hubbuck, J. R. "Numerical Forms." Journal of the London Mathematical Society 55, no. 1 (February 1997): 65–75. http://dx.doi.org/10.1112/s0024610796004395.

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39

Rodi, W. "Numerical methods." Journal of Wind Engineering and Industrial Aerodynamics 69-71 (July 1997): 131–32. http://dx.doi.org/10.1016/s0167-6105(97)00227-4.

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40

Essex, Christopher, Matt Davison, and Christian Schulzky. "Numerical monsters." ACM SIGSAM Bulletin 34, no. 4 (December 2000): 16–32. http://dx.doi.org/10.1145/377626.377635.

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41

Smith, D. K. "Numerical Optimization." Journal of the Operational Research Society 52, no. 2 (February 2001): 245. http://dx.doi.org/10.1057/palgrave.jors.2601183.

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42

Carbonnnel, Gilles. "Numerical geology." Geobios 22, no. 1 (January 1989): 129. http://dx.doi.org/10.1016/s0016-6995(89)80093-2.

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43

Portela, Artur. "Numerical quadrature." Engineering Analysis with Boundary Elements 6, no. 2 (June 1989): 115. http://dx.doi.org/10.1016/0955-7997(89)90011-8.

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44

Eslami, M., and A. Neyrame. "Numerical methods." Computational Mathematics and Modeling 22, no. 1 (January 2011): 92–97. http://dx.doi.org/10.1007/s10598-011-9091-0.

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45

Ramos, J. I. "Numerical Methods." Applied Mathematical Modelling 14, no. 8 (August 1990): 444. http://dx.doi.org/10.1016/0307-904x(90)90101-a.

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46

Brezinski, C. "Numerical analysis." Mathematics and Computers in Simulation 31, no. 6 (February 1990): 596. http://dx.doi.org/10.1016/0378-4754(90)90072-q.

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47

DeTar, DeLosF. "Numerical Recipes." Computers & Chemistry 13, no. 3 (January 1989): 297–98. http://dx.doi.org/10.1016/0097-8485(89)85017-x.

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48

Mandelbaum, Eric. "Numerical Architecture." Topics in Cognitive Science 5, no. 2 (March 4, 2013): 367–86. http://dx.doi.org/10.1111/tops.12014.

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49

Clarke, G. M., R. L. Burden, and J. D. Faires. "Numerical Analysis." Statistician 41, no. 1 (1992): 128. http://dx.doi.org/10.2307/2348648.

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50

G., W., M. Mori, and R. Piessens. "Numerical Quadrature." Mathematics of Computation 50, no. 181 (January 1988): 357. http://dx.doi.org/10.2307/2007947.

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