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Journal articles on the topic 'Simulation methods'

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Published: 4 June 2021
Last updated: 29 July 2024

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1

Ripley, B. D., and M. D. Kirkland. "Iterative simulation methods." Journal of Computational and Applied Mathematics 31, no. 1 (July 1990): 165–72. http://dx.doi.org/10.1016/0377-0427(90)90347-3.

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2

Fagbade, Adeyemi, and Stefan Heinz. "Continuous Eddy Simulation vs. Resolution-Imposing Simulation Methods for Turbulent Flows." Fluids 9, no. 1 (January 10, 2024): 22. http://dx.doi.org/10.3390/fluids9010022.

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The usual concept of simulation methods for turbulent flows is to impose a certain (partial) flow resolution. This concept becomes problematic away from limit regimes of no or an almost complete flow resolution: discrepancies between the imposed and actual flow resolution may imply an unreliable model behavior and high computational cost to compensate for simulation deficiencies. An exact mathematical approach based on variational analysis provides a solution to these problems. Minimal error continuous eddy simulation (CES) designed in this way enables simulations in which the model actively responds to variations in flow resolution by increasing or decreasing its contribution to the simulation as required. This paper presents the first application of CES methods to a moderately complex, relatively high Reynolds number turbulent flow simulation: the NASA wall-mounted hump flow. It is shown that CES performs equally well or better than almost resolving simulation methods at a little fraction of computational cost. Significant computational cost and performance advantages are reported in comparison to popular partially resolving simulation methods including detached eddy simulation and wall-modeled large eddy simulation. Characteristic features of the asymptotic flow structure are identified on the basis of CES simulations.
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3

Podolskaya, Nina A. "Network Simulation: Tasks and Methods of Their Solution." International Journal of Computer Theory and Engineering 6, no. 5 (October 2014): 392–95. http://dx.doi.org/10.7763/ijcte.2014.v6.896.

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4

Zäh, Michael F., and Alexander Schober. "Innovative welding simulation methods." ATZproduktion worldwide 3, no. 1 (February 2010): 32–36. http://dx.doi.org/10.1007/bf03224215.

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5

Millington, James D. A., and John Wainwright. "Mixed qualitative-simulation methods." Progress in Human Geography 41, no. 1 (July 10, 2016): 68–88. http://dx.doi.org/10.1177/0309132515627021.

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Across geography there has been variable engagement with the use of simulation and agent-based modelling. We argue that agent-based simulation provides a complementary method to investigate geographical issues which need not be used in ways that are epistemologically different in kind from some other approaches in contemporary geography. We propose mixed qualitative-simulation methods that iterate back-and-forth between ‘thick’ (qualitative) and ‘thin’ (simulation) approaches and between the theory and data they produce. These mixed methods accept simulation modelling as process and practice; a way of using computers with concepts and data to ensure social theory remains embedded in day-to-day geographical thinking.
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6

Andersen, Torben G. "SIMULATION-BASED ECONOMETRIC METHODS." Econometric Theory 16, no. 1 (February 2000): 131–38. http://dx.doi.org/10.1017/s0266466600001080.

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The accessibility of high-performance computing power has always influenced theoretical and applied econometrics. Gouriéroux and Monfort begin their recent offering, Simulation-Based Econometric Methods, with a stylized three-stage classification of the history of statistical econometrics. In the first stage, lasting through the 1960's, models and estimation methods were designed to produce closed-form expressions for the estimators. This spurred thorough investigation of the standard linear model, linear simultaneous equations with the associated instrumental variable techniques, and maximum likelihood estimation within the exponential family. During the 1970's and 1980's the development of powerful numerical optimization routines led to the exploration of procedures without closed-form solutions for the estimators. During this period the general theory of nonlinear statistical inference was developed, and nonlinear micro models such as limited dependent variable models and nonlinear time series models, e.g., ARCH, were explored. The associated estimation principles included maximum likelihood (beyond the exponential family), pseudo-maximum likelihood, nonlinear least squares, and generalized method of moments. Finally, the third stage considers problems without a tractable analytic criterion function. Such problems almost invariably arise from the need to evaluate high-dimensional integrals. The idea is to circumvent the associated numerical problems by a simulation-based approach. The main requirement is therefore that the model may be simulated given the parameters and the exogenous variables. The approach delivers simulated counterparts to standard estimation procedures and has inspired the development of entirely new procedures based on the principle of indirect inference.
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7

Tikhonov, V., and R. Veenhof. "GEM simulation methods development." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 478, no. 1-2 (February 2002): 452–59. http://dx.doi.org/10.1016/s0168-9002(01)01801-0.

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8

Guha, Ratan, and Mostafa Bassiouni. "Simulation Methods and Applications." Simulation Practice and Theory 9, no. 3-5 (April 2002): 91–93. http://dx.doi.org/10.1016/s0928-4869(01)00056-8.

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9

Elber, Ron. "Long-timescale simulation methods." Current Opinion in Structural Biology 15, no. 2 (April 2005): 151–56. http://dx.doi.org/10.1016/j.sbi.2005.02.004.

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10

Barrett, John H. "Methods of channeling simulation." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 44, no. 3 (January 1990): 367–72. http://dx.doi.org/10.1016/0168-583x(90)90652-b.

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11

GEORGE, E., J. GLIMM, X. L. LI, A. MARCHESE, Z. L. XU, J. W. GROVE, and DAVID H. SHARP. "Numerical methods for the determination of mixing." Laser and Particle Beams 21, no. 3 (July 2003): 437–42. http://dx.doi.org/10.1017/s0263034603213239.

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We present a Rayleigh–Taylor mixing rate simulation with an acceleration rate falling within the range of experiments. The simulation uses front tracking to prevent interfacial mass diffusion. We present evidence to support the assertion that the lower acceleration rate found in untracked simulations is caused, at least to a large extent, by a reduced buoyancy force due to numerical interfacial mass diffusion. Quantitative evidence includes results from a time-dependent Atwood number analysis of the diffusive simulation, which yields a renormalized mixing rate coefficient for the diffusive simulation in agreement with experiment. We also present the study of Richtmyer–Meshkov mixing in cylindrical geometry using the front tracking method and compare it with the experimental results.
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12

Winterstein, S. R., and R. Torhaug. "Extreme Jack-Up Response: Simulation and Nonlinear Analysis Methods." Journal of Offshore Mechanics and Arctic Engineering 118, no. 2 (May 1, 1996): 103–8. http://dx.doi.org/10.1115/1.2828817.

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The nonlinear dynamic response of a jack-up structure under random wave loads is considered. For a simplified jack-up model, average behavior and variability in extreme forces and responses are found from simulation over many 6-h seastates. Weibull and Hermite analytical models of response extremes are also presented and evaluated. These models use shorter, less expensive simulations to estimate a limited number of response statistics, such as moments or parameters of the response peak distribution, and fit analytical models to estimate global extremes. Necessary simulation lengths are established both for direct simulation of extremes, and for analytical extreme models.
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13

Chen, Lei. "Comparisons of Explicit and Implicit Finite Element Methods for Sheet Metal Forming." Advanced Materials Research 936 (June 2014): 1836–39. http://dx.doi.org/10.4028/www.scientific.net/amr.936.1836.

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Sheet metal forming is one of the most commonly practiced fabrication processes in industry. Numerical simulations of the complex parts are possible by finite element method in the past thirty years. The most important problem of the simulation is the reliability of the model. Static implicit method (SI) and dynamic explicit method (DE) were used to simulation sheet metal forming process. It was found that simulation speed in dynamic explicit software has large effect on the simulation results. The best simulation speed is 5~10 m/s. Compared with the simulation and experimental results of thickness, draw-in and CPU time, the DE method is preferred.
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14

Ishigami, Toshihiko. "Simulation Methods for Lamp Development." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 83, no. 1 (1999): 19–22. http://dx.doi.org/10.2150/jieij1980.83.1_19.

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15

Kanevskaya, R. D., and A. V. Novikov. "Methods of acid fracturing simulation." Automation, Telemechanization and Communication in Oil Industry, no. 3 (2018): 28–34. http://dx.doi.org/10.30713/0132-2222-2018-3-28-34.

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16

Davis, Jason P., Kathleen M. Eisenhardt, and Christopher B. Bingham. "Developing Theory Through Simulation Methods." Academy of Management Review 32, no. 2 (April 2007): 480–99. http://dx.doi.org/10.5465/amr.2007.24351453.

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17

Apithy, H., Y. Bouslimaniet, and H. Hamam. "Simulation methods in optical propagation." Canadian Journal of Electrical and Computer Engineering 30, no. 1 (2005): 39–48. http://dx.doi.org/10.1109/cjece.2005.1532605.

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18

Haile, J. M., Ian Johnston, A. John Mallinckrodt, and Susan McKay. "Molecular Dynamics Simulation: Elementary Methods." Computers in Physics 7, no. 6 (1993): 625. http://dx.doi.org/10.1063/1.4823234.

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19

Mezencev, Konstantin Nikolaevich, and Punam Jha. "Simulation Methods of Computer Networks." International Journal of Advanced Studies 4, no. 3 (January 14, 2015): 9. http://dx.doi.org/10.12731/2227-930x-2014-3-2.

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20

Мезенцев, Константин Николаевич, and Джха Пунам. "Simulation methods of computer networks." Automation and Control in Technical Systems, no. 2 (January 4, 2015): 29. http://dx.doi.org/10.12731/2306-1561-2014-2-4.

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21

Kadau, Kai, John L. Barber, Timothy C. Germann, Brad L. Holian, and Berni J. Alder. "Atomistic methods in fluid simulation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1916 (April 13, 2010): 1547–60. http://dx.doi.org/10.1098/rsta.2009.0218.

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Atomistic methods, such as molecular dynamics and direct simulation Monte Carlo, constitute a powerful and growing set of techniques for fluid-dynamics simulation. The more fundamental nature of such methods, which exhibit nonlinear transport effects and small-scale fluctuations, extends their modelling accuracy to a significantly wider range of scales and regimes than the more traditional Navier–Stokes-based continuum fluid-simulation techniques. In this paper, we describe the current state of the art in atomistic fluid simulation, from both a theoretical and a computational standpoint, and outline the advantages and limitations of such methods. In addition, we present an overview of some recent atomistic-simulation results on fluid instabilities and on the physical scaling of atomistic techniques. Finally, we suggest possible avenues of future research in the field.
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22

KELTON, W. DAVID. "Random Initialization Methods in Simulation." IIE Transactions 21, no. 4 (December 1989): 355–67. http://dx.doi.org/10.1080/07408178908966242.

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23

Giraudo, Marı́a Teresa, and Laura Sacerdote. "Simulation methods in neuronal modelling." Biosystems 48, no. 1-3 (November 1998): 77–83. http://dx.doi.org/10.1016/s0303-2647(98)00052-5.

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24

Schmidt, G., and G. Lappus. "Digital Simulation Methods — A Tutorial." IFAC Proceedings Volumes 18, no. 11 (September 1985): 83–93. http://dx.doi.org/10.1016/s1474-6670(17)60113-7.

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25

Feijóo, Andrés, and Daniel Villanueva. "Assessing wind speed simulation methods." Renewable and Sustainable Energy Reviews 56 (April 2016): 473–83. http://dx.doi.org/10.1016/j.rser.2015.11.094.

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26

Heiss, Florian. "Discrete Choice Methods with Simulation." Econometric Reviews 35, no. 4 (February 6, 2016): 688–92. http://dx.doi.org/10.1080/07474938.2014.975634.

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27

Seleim, A. Azab, and T. AlGeddawy. "Simulation Methods for Changeable Manufacturing." Procedia CIRP 3 (2012): 179–84. http://dx.doi.org/10.1016/j.procir.2012.07.032.

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28

Popov, V. L., and S. G. Psakhie. "Numerical simulation methods in tribology." Tribology International 40, no. 6 (June 2007): 916–23. http://dx.doi.org/10.1016/j.triboint.2006.02.020.

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29

Guilleaume, C., and A. Brosius. "Simulation methods for skew rolling." Procedia Manufacturing 27 (2019): 1–6. http://dx.doi.org/10.1016/j.promfg.2018.12.035.

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30

Yanez, Javier. "Neural Network and Simulation Methods." Neurocomputing 9, no. 2 (October 1995): 218–19. http://dx.doi.org/10.1016/0925-2312(95)90021-7.

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31

Ramos, J. I. "Computational Methods for Process Simulation." Applied Mathematical Modelling 14, no. 8 (August 1990): 445. http://dx.doi.org/10.1016/0307-904x(90)90103-c.

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32

Chronister, Connie, and Diane Brown. "Comparison of Simulation Debriefing Methods." Clinical Simulation in Nursing 8, no. 7 (September 2012): e281-e288. http://dx.doi.org/10.1016/j.ecns.2010.12.005.

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33

Joppich, W., and S. Mijalković. "Multigrid methods for process simulation." Microelectronics Journal 26, no. 2-3 (March 1995): xxvii—xxviii. http://dx.doi.org/10.1016/0026-2692(95)90020-9.

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34

Wagner, Janet M., Uri Shamir, and David H. Marks. "Water Distribution Reliability: Simulation Methods." Journal of Water Resources Planning and Management 114, no. 3 (May 1988): 276–94. http://dx.doi.org/10.1061/(asce)0733-9496(1988)114:3(276).

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35

Pb. "Molecular dynamics simulation, elementary methods." Journal of Molecular Structure: THEOCHEM 288, no. 3 (December 1993): 287–88. http://dx.doi.org/10.1016/0166-1280(93)87060-q.

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36

Varakin, A. I., V. V. Mazur, N. V. Arkhipova, and Yu V. Seryanov. "Simulation methods in biophysical pharmacokinetics." Biomedical Engineering 41, no. 3 (May 2007): 103–7. http://dx.doi.org/10.1007/s10527-007-0022-5.

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37

Paterson, W. R. "Computational methods for Process simulation." Chemical Engineering Science 47, no. 8 (June 1992): 2129–30. http://dx.doi.org/10.1016/0009-2509(92)80336-b.

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38

Gaffney, Betty J., and Harris J. Silverstone. "Simulation Methods for Looping Transitions." Journal of Magnetic Resonance 134, no. 1 (September 1998): 57–66. http://dx.doi.org/10.1006/jmre.1998.1526.

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39

Eigenberger, G. "Computational Methods for Process Simulation." Chemical Engineering and Processing: Process Intensification 30, no. 1 (July 1991): 59. http://dx.doi.org/10.1016/0255-2701(91)80010-m.

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40

Liu, Shilong, Ioan Nistor, and Majid Mohammadian. "Evaluation of the Solid Boundary Treatment Methods in SPH." International Journal of Ocean and Coastal Engineering 01, no. 02 (June 2018): 1840002. http://dx.doi.org/10.1142/s252980701840002x.

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The smoothed particle hydrodynamics (SPH) method has been proved as a powerful algorithm for fluid mechanics, especially in the simulation of free surface flows with high speeds or drastic impacts. The solid boundary treatment method is important for the accuracy and stability of the numerical results, as the support domain of fluid particles is truncated near the vicinity of the boundary. This paper presents two commonly used methods for simulating a solid boundary in SPH simulations. Emphasis is placed on the description of the methods, definition of the boundary particles’ parameters, and discussion of their advantages and shortcomings. The classical dam break simulation is conducted using self-developed code and open source models such as DualSPHysics and PySPH in order to investigate the effects of the boundary methods. The results show that methods based on dynamic boundary particles can simulate the free water surface well with a good agreement with experimental results. The conclusions can also be used in research for boundary implementation methods for practical ocean and coastal engineering problems with free surface flows.
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41

Paulovics, László, Jan Rohde-Brandenburger, and Csaba Tóth-Nagy. "Timing chain wear investigation methods: Review." FME Transactions 50, no. 3 (2022): 461–72. http://dx.doi.org/10.5937/fme2203461p.

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Several methods are used for investigating timing chain wear, from fired engine dynamometer tests through tribological model tests to simulations. Research over the past decade has shown that component or tribometer tests can replace expensive engine dynamometer tests in many cases. Simulation methods can further reduce the cost and time of development. Simulation models require experimentally defined input parameters; therefore, experiment-based methods cannot be completely avoided. However, a comprehensive comparison or validation of the various experimental and simulation techniques is difficult, as the literature on the topic is relatively scarce. This study aims to give a systematic comparison of the results of several investigation methods of timing chain wear, supported by data measured at Széchenyi István University, such as fired engine dynamometer tests, cold dynamometer tests, component tests, and tribometer tests, presenting their benefits and limitations, where possible through examples and results. The study also provides an insight into the compatibility of different measurement methods.
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42

MARK, ANDREAS, ERIK SVENNING, ROBERT RUNDQVIST, FREDRIK EDELVIK, ERIK GLATT, STEFAN RIEF, ANDREAS WIEGMANN, et al. "Microstructure simulation of early paper forming using immersed boundary methods." November 2011 11, no. 11 (December 1, 2011): 23–30. http://dx.doi.org/10.32964/10.32964/tj10.11.23.

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Paper forming is the first step in the paper machine where a fiber suspension leaves the headbox and flows through a forming fabric. Complex physical phenomena occur as the paper forms, during which fibers, fillers, fines, and chemicals added to the suspension interact. Understanding this process is important for the development of improved paper products because the configuration of the fibers during this step greatly influences the final paper quality. Because the effective paper properties depend on the microstructure of the fiber web, a continuum model is inadequate to explain the process and the properties of each fiber need to be accounted for in simulations. This study describes a new framework for microstructure simulation of early paper forming. The simulation framework includes a Navier-Stokes solver and immersed boundary methods to resolve the flow around the fibers. The fibers were modeled with a finite element discretization of the Euler-Bernoulli beam equation in a co-rotational formulation. The contact model is based on a penalty method and includes friction and elastic and inelastic collisions. We validated the fiber model and the contact model against demanding test cases from the literature, with excellent results. The fluid-structure interaction in the model was examined by simulating an elastic beam oscillating in a cross flow. We also simulated early paper formation to demonstrate the potential of the proposed framework.
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43

Yang, Song, Xiaoguang Zhang, Lixia Xi, and Wenyu Peng. "Novel methods for the simulation of impairments in optical network." Chinese Optics Letters 10, S2 (2012): S20608. http://dx.doi.org/10.3788/col201210.s20608.

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44

Yang, Song, Xiaoguang Zhang, Lixia Xi, and Wenyu Peng. "Novel methods for the simulation of impairments in optical network." Chinese Optics Letters 10, S2 (2012): S20608. http://dx.doi.org/10.3788/col201210.s20608.

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45

Song Yang, Song Yang, Xiaoguang Zhang Xiaoguang Zhang, Lixia Xi Lixia Xi, and Wenyu Peng Wenyu Peng. "Novel methods for the simulation of impairments in optical network." Chinese Optics Letters 10, s2 (2012): S20608–320610. http://dx.doi.org/10.3788/col201210.s20608.

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46

Novoseletskyy, Oleksandr, Sabina Jurkaitienė, and Ostap Melnyk. "SIMULATION OF THE EXCHANGE RATE USING ECONOMIC AND MATHEMATICAL METHODS." Scientific Notes of Ostroh Academy National University, "Economics" Series 1, no. 27(55) (December 22, 2022): 104–15. http://dx.doi.org/10.25264/2311-5149-2022-27(55)-104-115.

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The article is devoted to a comparative analysis of the use of adaptive methods and models, autoregressive models and neural networks in forecasting the exchange rate of the main reserve currencies: the euro, the Swiss franc, the Japanese yen and the British pound against the US dollar. In the course of the research, the works of Ukrainian and foreign scientists on this topic were reviewed and it was determined that the most used methods and models in forecasting the exchange rate based on time series are autoregression models (represented by ARIMA and SARIMA models), neural networks (represented by MLP and ELM architectures) and exponential smoothing methods. In the process of building the models, time series were examined for stationarity based on the Dickey-Fuller test and additive decomposition of the studied time series was performed to determine their main components (trend, seasonality, random component). Construction of forecast models was carried out, on the basis of which their comparative analysis took place. The main shortcomings and problems of using the selected methods are demonstrated and the best predictive models are determined. It is determined that the main drawback of all time series forecasting methods is their "adaptability" to the input data, and the desire to improve the estimation characteristics of the models as a result can lead to the fact that the forecasts differ significantly from the actual values. It was also determined that for forecasting the exchange rate of selected currency pairs, neural networks are best suited, which have both high evaluation characteristics and correspondence of the forecast to real values, and the MLP network shows better results compared to the ELM network. High evaluation characteristics are also demonstrated by adaptive models. However, the linear nature of the forecast does not allow adaptive models to make an accurate forecast in the long term. Although autoregressive models show worse estimation characteristics, they outperform neural networks in terms of matching real values for individual currency pairs.
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47

Rajput, Abhishek, Alessandro Roggero, and Nathan Wiebe. "Hybridized Methods for Quantum Simulation in the Interaction Picture." Quantum 6 (August 17, 2022): 780. http://dx.doi.org/10.22331/q-2022-08-17-780.

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Conventional methods of quantum simulation involve trade-offs that limit their applicability to specific contexts where their use is optimal. In particular, the interaction picture simulation has been found to provide substantial asymptotic advantages for some Hamiltonians, but incurs prohibitive constant factors and is incompatible with methods like qubitization. We provide a framework that allows different simulation methods to be hybridized and thereby improve performance for interaction picture simulations over known algorithms. These approaches show asymptotic improvements over the individual methods that comprise them and further make interaction picture simulation methods practical in the near term. Physical applications of these hybridized methods yield a gate complexity scaling as log2⁡Λ in the electric cutoff Λ for the Schwinger Model and independent of the electron density for collective neutrino oscillations, outperforming the scaling for all current algorithms with these parameters. For the general problem of Hamiltonian simulation subject to dynamical constraints, these methods yield a query complexity independent of the penalty parameter λ used to impose an energy cost on time-evolution into an unphysical subspace.
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48

Lipecki, T., and A. Flaga. "Application of Simulation Methods of Stochastic Processes to Vortex Excitation." Archives of Civil Engineering 63, no. 1 (March 28, 2017): 77–98. http://dx.doi.org/10.1515/ace-2017-0006.

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AbstractA description of direct simulation of crosswind loads caused by critical vortex excitation and the response of the structure to these loads are presented in this paper. Tower-like structures of circular cross-sections are considered. A proposed mathematical model of vortex excitation has been numerically implemented and a selfserving computer program was created for the purpose. This software, cooperating with the FEM system, allows for a simulation of a crosswind load and lateral response in real time, meaning that at each time step of the calculations the load is generated using information regarding displacements seen beforehand. A detailed description of the mathematical model is neglected in this paper, which is focused on numerical simulations. WAWS and AR methods are used in simulations.
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49

Reichherzer, P., and J. Becker Tjus. "Efficient charged particle propagation methods." Journal of Physics: Conference Series 2438, no. 1 (February 1, 2023): 012138. http://dx.doi.org/10.1088/1742-6596/2438/1/012138.

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Abstract In astrophysics, the search for sources of the highest-energy cosmic rays continues. For further progress, not only ever better observatories but also ever more realistic numerical simulations are needed. We compare different approaches for numerical test simulations of ultra-high-energy cosmic rays in the intergalactic magnetic field and show that all methods provide correct statistical propagation characteristics of the particles in means of their diffusive behaviour. Through convergence tests, we show that the necessary requirements for the methods differ and ultimately reveal significant differences in the required simulation time.
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50

Poteriailo, L. O., V. V. Protsjuk, and K. I. Kravtsiv. "KNOWLEDGE-ORIENTED DECISION-MAKING METHODS IN SIMULATIONS OF TECHNOLOGICAL PROCESS SIMULATION." METHODS AND DEVICES OF QUALITY CONTROL, no. 2(45) (December 28, 2020): 132–45. http://dx.doi.org/10.31471/1993-9981-2020-2(45)-132-145.

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The article presents the results of research in the field of simulation of drilling processes using modern computer modeling. The main parameters of the drilling process are determined as theoretical considerations aimed at introducing concepts related to simulation modeling and computer modeling in drilling. The analysis of the models used in the simulation of drilling processes is carried out. The basic characteristics of the simulator modeling are highlighted, which provides a holistic perception of technological processes, as well as any degree of their detailing. The main methods of modeling used in the development of automated control systems and simulators of industrial installations, ways of developing their software and some aspects of creating effective software and computer systems are presented. Further, a review of the essence of technological simulators is carried out, from a technical point of view, the current state of training systems for training operators of technological processes is highlighted. The differences between simulators and other teaching aids and the specifics of simulators for technical processes are presented. The characteristic features and prospects of simulator building in various industries are briefly described. The compulsory components of the simulators and the quality criteria of the simulators are determined. A study of the existing technical solutions for systems of the "Drilling simulators" class was carried out. Conclusions are made regarding the practical aspects of using modern engineering solutions for drilling simulators. The advantages are determined as a result of using simulators in various types of operational-tactical exercises, as the main form of improving the optimization of drilling control both for production tasks and training tasks. Particular emphasis is placed on the Drillsimm5000 simulator, which is used in the training of drilling specialists at the Ivano-Frankivsk Technical National University of Oil and Gas. From the standpoint of various services of the enterprise interested in purchasing simulators, the potential benefits of computer training and the tasks that need to be solved for the successful implementation of simulators are analyzed, problems associated with their implementation are presented.
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