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Littérature scientifique sur le sujet « Stochastic cycle »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Stochastic cycle"

Netzer, Corinna, Michal Pasternak, Lars Seidel, Frédéric Ravet, and Fabian Mauss. "Computationally efficient prediction of cycle-to-cycle variations in spark-ignition engines." International Journal of Engine Research 21, no. 4 (2019): 649–63. http://dx.doi.org/10.1177/1468087419856493.

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Cycle-to-cycle variations are important to consider in the development of spark-ignition engines to further increase fuel conversion efficiency. Direct numerical simulation and large eddy simulation can predict the stochastics of flows and therefore cycle-to-cycle variations. However, the computational costs are too high for engineering purposes if detailed chemistry is applied. Detailed chemistry can predict the fuels’ tendency to auto-ignite for different octane ratings as well as locally changing thermodynamic and chemical conditions which is a prerequisite for the analysis of knocking comb

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Bashkirtseva, Irina, and Lev Ryashko. "Stochastic Bifurcations and Noise-Induced Chaos in a Dynamic Prey–Predator Plankton System." International Journal of Bifurcation and Chaos 24, no. 09 (2014): 1450109. http://dx.doi.org/10.1142/s0218127414501090.

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We consider the stochastic Truscott–Brindley dynamical model of the interacting populations of prey and predator. We study a new phenomenon of the stochastic cycle splitting. In a zone of Canard cycles, using the stochastic sensitivity function technique, we find a critical value of the parameter corresponding to the supersensitive cycle. In the neighborhood of this critical value, a comparative parametrical analysis of the phenomenon of the stochastic cycle splitting is performed. It is shown that the bifurcation of the stochastic cycle splitting is accompanied by the noise-induced chaotizati

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Brandenburg, Axel, and Gustavo Guerrero. "Cycles and cycle modulations." Proceedings of the International Astronomical Union 7, S286 (2011): 37–48. http://dx.doi.org/10.1017/s1743921312004619.

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AbstractSome selected concepts of the solar activity cycle are reviewed. Cycle modulations through a stochastic α effect are being identified with limited scale separation ratios. Three-dimensional turbulence simulations with helicity and shear are compared at two different scale separation ratios. In both cases the level of fluctuations shows relatively little variation with the dynamo cycle. Prospects for a shallow origin of sunspots are discussed in terms of the negative effective magnetic pressure instability. Tilt angles of bipolar active regions are discussed as a consequence of shear ra

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BASHKIRTSEVA, IRINA, LEV RYASHKO, and EUDOKIA SLEPUKHINA. "NOISE-INDUCED OSCILLATING BISTABILITY AND TRANSITION TO CHAOS IN FITZHUGH–NAGUMO MODEL." Fluctuation and Noise Letters 13, no. 01 (2014): 1450004. http://dx.doi.org/10.1142/s0219477514500047.

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Stochastic dynamics of the FitzHugh–Nagumo (FHN) neuron model in the limit cycles zone is studied. For weak noise, random trajectories are concentrated in the small neighborhood of the unforced deterministic cycle. As the noise intensity increases, in the Canard-like cycles zone of the FHN model, a bundle of the stochastic trajectories begins to split into two parts. This phenomenon is investigated using probability density functions for the distribution of random trajectories. It is shown that the intensity of noise generating this splitting bifurcation significantly depends on the stochastic

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BASHKIRTSEVA, I., L. RYASHKO, and P. STIKHIN. "NOISE-INDUCED BACKWARD BIFURCATIONS OF STOCHASTIC 3D-CYCLES." Fluctuation and Noise Letters 09, no. 01 (2010): 89–106. http://dx.doi.org/10.1142/s0219477510000095.

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We study stochastically forced multiple limit cycles of nonlinear dynamical systems in a period-doubling bifurcation zone. Noise-induced transitions between separate parts of the cycle are considered. A phenomenon of a decreasing of the stochastic cycle multiplicity with a noise intensity growth is investigated. We call it by a backward stochastic bifurcation (BSB). In this paper, for the BSB analysis we suggest a stochastic sensitivity function technique. As a result, a method for the estimation of critical values of noise intensity corresponding to BSB is proposed. The constructive possibili

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SOWERS, RICHARD B. "STOCHASTIC AVERAGING NEAR LONG HETEROCLINIC ORBITS." Stochastics and Dynamics 07, no. 02 (2007): 187–228. http://dx.doi.org/10.1142/s0219493707001974.

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We refine some of the bounds of [10]. There, we considered the effect of diffusive perturbations on a two-dimensional ODE with a heteroclinic cycle. We constructed corrector functions for asymptotically "glueing" together behavior of periodic orbits in the boundary layer near the heteroclinic cycle. Here, we adapt the analysis of [10] to allow for "long" heteroclinic cycles.

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YU. RYAGIN, MIKHAIL, and LEV B. RYASHKO. "THE ANALYSIS OF THE STOCHASTICALLY FORCED PERIODIC ATTRACTORS FOR CHUA'S CIRCUIT." International Journal of Bifurcation and Chaos 14, no. 11 (2004): 3981–87. http://dx.doi.org/10.1142/s0218127404011600.

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This report shows the results of sensitivity analysis for Chua's circuit periodic attractors under small disturbances. Sensitivity analysis is based on the quasipotential method. Quasipotential's first approximation in the neighborhood of the limit cycle is defined by the matrix of orbital quadratic form, named stochastic sensitivity function (SSF). SSF is defined for the points of the nonperturbed limit cycle and can be computed using the numerical algorithm. Stochastic sensitivity of the limit cycles for the Chua's circuit period doubling cascade is investigated. The growth of the stochastic

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Melchionna, Andrew. "Stochastic sandpile on a cycle." Journal of Physics A: Mathematical and Theoretical 55, no. 19 (2022): 195001. http://dx.doi.org/10.1088/1751-8121/ac61b9.

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Abstract In the stochastic sandpile (SS) model on a graph, particles interact pairwise as follows: if two particles occupy the same vertex, they must each take an independent random walk step with some probability 0 < p < 1 of not moving. These interactions continue until each site has no more than one particle on it. We provide a formal coupling between the SS and the activated random walk models, and we use the coupling to show that for the SS with n particles on the cycle graph Z n , the system stabilizes in O(n 3) time for all initial particle configurations, provided that p(n) tends

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Luvsantseren, Purevdolgor, Enkhbayar Purevjav, and Khenmedeh Lochin. "Stochastic simulation of cell cycle." Advanced Studies in Biology 5 (2013): 1–9. http://dx.doi.org/10.12988/asb.2013.13001.

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Balasubramanian, K., V. Parameswaran, and S. B. Rao. "Characterization of Cycle Stochastic Graphs." Electronic Notes in Discrete Mathematics 15 (May 2003): 36. http://dx.doi.org/10.1016/s1571-0653(04)00520-7.

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Thèses sur le sujet "Stochastic cycle"

He, Enuo. "Stochastic modelling of the cell cycle." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:04185cde-85af-4e24-8d06-94b865771cf1.

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Precise regulation of cell cycle events by the Cdk-control network is essential for cell proliferation and the perpetuation of life. The unidirectionality of cell cycle progression is governed by several critical irreversible transitions: the G1-to-S transition, the G2-to-M transition, and the M-to-G1 transition. Recent experimental and theoretical evidence has pulled into question the consensus view that irreversible protein degradation causes the irreversibility of those transitions. A new view has started to emerge, which explains the irreversibility of cell cycle transitions as a consequen

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Posadas, Sergio. "Stochastic simulation of a Commander's decision cycle (SSIM CODE)." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA392113.

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Thesis (M.S. in Operations Research) Naval Postgraduate School, June 2001. Thesis advisor(s): Paulo, Eugene P. ; Olson, Allen S. "June 2001." Includes bibliographical references (p. 111-115). Also available in print.

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VanDoorne, Rick. "Stochastic rail life cycle cost maintenance modeling using Monte Carlo simulation." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/61343.

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The objective of this study was to quantify and determine trends in the uncertainty in the life cycle cost (LCC) associated with the maintenance and renewal (M&R) of the rail of a railway track under a fixed set of input parameters and conditions. Rail maintenance models were identified in the literature which use the mean or expected value of the input distributions to determine a corresponding mean or expected LCC. Although these models display important trends with regard to input parameters such as inspection intervals, they provide no means to quantify the uncertainty related to maintenan

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McNally, Richard J. Q. "Stochastic modelling of the reproductive cycle in cows and related estimation problems." Thesis, University of Reading, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.252896.

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Cheaitou, Ali. "Stochastic models for production-Inventory planning : application to short life-cycle products." Châtenay-Malabry, Ecole centrale de Paris, 2008. http://www.theses.fr/2008ECAP1066.

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Dans le domaine du « Supply Chain Management » la source principale d’incertitude est la demande future. L’impact de l’incertitude de lademande sur les performances de la « Supply Chain » est important: par exemple, le taux mondial de rupture de stock, dans l’industrie dedistribution était en 2007 de 8. 3%. De l’autre côté, le taux mondial de produits invendus, dans la grande distribution, était en 2003 de 1%. Ces deux types de coûts, qui sont dus essentiellement à l’incertitude de la demande, représentent des pertes significatives pour lesdifférents acteurs de la « Supply Chain ». Dans cette

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Chen, Minghan. "Stochastic Modeling and Simulation of Multiscale Biochemical Systems." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/90898.

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Numerous challenges arise in modeling and simulation as biochemical networks are discovered with increasing complexities and unknown mechanisms. With the improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for quantitative stochastic models for gene and protein networks at cellular levels that match well with the data and account for cellular noise. This dissertation studies a stochastic spatiotemporal model of the Caulobacter crescentus cell cycle. A two-dimensional model based on a Turing mechanism is in

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Davis, Neil Nathaniel. "Dynamic and Stochastic Modeling of Various Components of the Hydrological Cycle for East Africa." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-05032007-094125/.

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This research has investigated the ability to model precipitation over East Africa using the RegCM regional climate model, and the ability of a stochastic model to predict Lake Victoria lake level one season in advance. The stochastic model was built using precipitation, sea surface temperatures and temperature, and provides detail about the steps used to develop the model. Precipitation modeling was carried out using RegCM and several convective schemes were compared to determine which performed best for East Africa. Additionally the microphysical scheme SUBEX was investigated thoroughly and

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Kotze, Kevin Lawrence. "The South African business cycle and the application of dynamic stochastic general equilibrium models." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/96055.

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Thesis (PhD)--Stellenbosch University, 2014. ENGLISH ABSTRACT: This dissertation considers the use of Dynamic Stochastic General Equilibrium (DSGE) models for the analysis of South African macroeconomic business cycle phenomena. It includes four separate, but interrelated parts, which follow a logical sequence. The rst part motivates the use of these models before establishing the theoretical foundations for these models. The theoretical foundations are accompanied by detailed derivations that are used to construct a model for a small open economy. The second part considers the pro

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Boone, Laurence. "An assessment of trend extraction techniques : application to time series decomposition of business cycle and endogenous technical progress." Thesis, London Business School (University of London), 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295884.

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Fonseca, Julia Fernandes Araújo da. "Aggregate uncertainty, disappointment aversion and the business cycle." reponame:Repositório Institucional do FGV, 2013. http://hdl.handle.net/10438/10940.

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Submitted by Júlia Fonseca (julia.f.fonseca@gmail.com) on 2013-06-24T17:08:45Z No. of bitstreams: 1 Julia Fonseca.pdf: 901363 bytes, checksum: 4df97de4c5783eb1e3f3acea7c9e8e25 (MD5) Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2013-06-27T12:57:48Z (GMT) No. of bitstreams: 1 Julia Fonseca.pdf: 901363 bytes, checksum: 4df97de4c5783eb1e3f3acea7c9e8e25 (MD5) Made available in DSpace on 2013-06-27T12:58:06Z (GMT). No. of bitstreams: 1 Julia Fonseca.pdf: 901363 bytes, checksum: 4df97de4c5783eb1e3f3acea7c9e8e25 (MD5) Previous issue date: 2013-06-17 We inves

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Livres sur le sujet "Stochastic cycle"

Jonsson, Gunnar. Stochastic fiscal policy and the Swedish business cycle. Stockholm University, Institute for International Economic Studies, 1995.

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Attfield, C. L. F. Stochastic trends and the business cycle in the UK. Bristol University, Department of Economics, 1992.

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Rotemberg, Julio. Is the business cycle a necessary consequence of stochastic growth? Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1994.

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Fernandez-Corugedo, Emilio. Imperfect information and the aggregate stochastic implications of the life cycle hypothesis. University of Bristol, Department of Economics, 1999.

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Lee, Danny C. The stochastic life-cycle model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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B, Hyman Jeffrey, and Intermountain Research Station (Ogden, Utah), eds. The Stochastic Life-Cycle Model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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Lee, Danny C. The stochastic life-cycle model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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Pemberton, James. Attainable non-optimality or unattainable optimality: A new approach to stochastic life cycle problems. University of Reading, Dept. of Economics, 1992.

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Chapitres de livres sur le sujet "Stochastic cycle"

Mura, Ivan. "Cell Cycle Modeling, Stochastic Methods." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_25.

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Ullah, Mukhtar, and Olaf Wolkenhauer. "The 2MA Cell Cycle Model." In Stochastic Approaches for Systems Biology. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0478-1_7.

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Kalpazidou, Sophia L. "Cycle Representations of Recurrent Denumerable Markov Chains." In Stochastic Modeling and Applied Probability. Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4757-3929-9_3.

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Heijungs, Reinout. "Statistical Analysis of Non-stochastic LCA." In Probability, Statistics and Life Cycle Assessment. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-49317-1_13.

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Verdonck, Freek, Herwig Bruneel, and Sabine Wittevrongel. "A Variable-Cycle Traffic Light Queue." In Computer Performance Engineering and Stochastic Modelling. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43185-2_5.

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Yoshimura, Kazuyuki. "Phase Reduction of Stochastic Limit-Cycle Oscillators." In Reviews of Nonlinear Dynamics and Complexity. Wiley-VCH Verlag GmbH & Co. KGaA, 2010. http://dx.doi.org/10.1002/9783527630967.ch3.

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Kalpazidou, S. "Cycle Representations of Markov Processes: An Application to Rotational Partitions." In Stochastic Processes and Related Topics. Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-2030-5_14.

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Grashorn, J., M. Broggi, L. Chamoin, and M. Beer. "Efficient posterior estimation for stochastic SHM using transport maps." In Life-Cycle of Structures and Infrastructure Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003323020-82.

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Kitahara, M., T. Kitahara, S. Bi, M. Broggi, and M. Beer. "Distribution-free stochastic model updating with staircase density functions." In Life-Cycle of Structures and Infrastructure Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003323020-81.

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Liu, B., I. B. Muhit, and V. Sarhosis. "Stochastic load-carrying capacity assessment of brick masonry arch bridges." In Life-Cycle of Structures and Infrastructure Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003323020-171.

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Actes de conférences sur le sujet "Stochastic cycle"

Ratanakuakangwan, Sudlop, and Tansiphorn Na Nan. "Clean Energy-farming Model under Uncertainty Using Stochastic Optimization and Life Cycle Cost Analysis." In 2024 11th International Conference on Power and Energy Systems Engineering (CPESE). IEEE, 2024. https://doi.org/10.1109/cpese62584.2024.10841227.

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Weaver, Brian J. "Data-Driven Stochastic Modeling of Dual-Frequency GNSS Measurements Using Cycle Slip Parameter Variance." In 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024). Institute of Navigation, 2024. http://dx.doi.org/10.33012/2024.19894.

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Nieto, César, Sayeh Rezaee, Cesar Augusto Vargas-Garcia, and Abhyudai Singh. "Joint Distribution Dynamics of Cell Cycle Variables in Exponentially-Growing Cells with Stochastic Division." In 2025 33rd Mediterranean Conference on Control and Automation (MED). IEEE, 2025. https://doi.org/10.1109/med64031.2025.11073330.

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Li, Yaohan, Deming Zhu, and You Dong. "Adapting to extreme risk of coastal bridges under typhoons in a life-cycle context." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.3258.

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Coastal bridges in tropical cyclone-prone regions face significant risks from the combined effects of storm surge and wave loads, which are further amplified by uncertainties associated with climate change. As climate change drives increases in the frequency and intensity of extreme weather events, the long-term risk to these critical infrastructures is expected to escalate, threatening financial stability, societal well-being, and infrastructural reliability. This study develops a framework to assess the extreme risk of coastal bridges in a life-cycle context, accounting for both tra

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Sydberger, T., J. D. Edwards, and K. J. Mørk. "A Probabilistic Approach to Prediction of CO2-Corrosion, and Its Application to Life Cycle Cost Analyses of Oil and Gas Equipment." In CORROSION 1995. NACE International, 1995. https://doi.org/10.5006/c1995-95065.

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Abstract Unduly conservative predictions of CO2-corrosion may prevent cost-effective solutions for corrosion control. Similarly, field experience has demonstrated that over-optimistic assumptions of the efficiency of planned corrosion mitigation may cause excessive costs not anticipated during the initial design; including monitoring, maintenance, repair and early condemnation. This paper propounds a probabilistic approach to the design of CO2-corrosion control where both the prediction of CO2-corrosion rate and inhibitor efficiency factors are treated as stochastic parameters, i.e. their reli

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E., Garavaglia. "Possible Application of the Markov Renewal Processes to the Life-Cycle Assessment of Deteriorating Structure." In 6th International Conference on Computational Stochastic Mechanics. Research Publishing Services, 2011. http://dx.doi.org/10.3850/978-981-08-7619-7_p028.

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Ahn, Tae-Hyuk, and Adrian Sandu. "Parallel stochastic simulations of budding yeast cell cycle." In the First ACM International Conference. ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854811.

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Iqbal, Muzammil, Ahmed Sharkawy, Usman Hameed, and Phillip Christie. "Stochastic wire length sampling for cycle time estimation." In the 2002 international workshop. ACM Press, 2002. http://dx.doi.org/10.1145/505348.505367.

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Han, Hongchen, Hongli Wang, Jia Xu, and Zhiwen Zhu. "Reliability Analysis Based on Stochastic Model of Business Cycle." In 2008 IEEE Symposium on Advanced Management of Information for Globalized Enterprises, AMIGE. IEEE, 2008. http://dx.doi.org/10.1109/amige.2008.ecp.69.

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Youn, L. T., and Koung Hee Leem. "Stochastic model for operation of bottoming-cycle cogeneration facility." In 2005 International Conference on Future Power Systems. IEEE, 2005. http://dx.doi.org/10.1109/fps.2005.204271.

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Rapports d'organisations sur le sujet "Stochastic cycle"

Frey, H., and E. Rubin. Stochastic modeling of coal gasification combined cycle systems: Cost models for selected integrated gasification combined cycle (IGCC) systems. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6204034.

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Melby, Jeffrey, Thomas Massey, Fatima Diop, et al. Coastal Texas Protection and Restoration Feasibility Study : Coastal Texas flood risk assessment : hydrodynamic response and beach morphology. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41051.

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The US Army Corps of Engineers, Galveston District, is executing the Coastal Texas Protection and Restoration Feasibility Study coastal storm risk management (CSRM) project for the region. The project is currently in the feasibility phase. The primary goal is to develop CSRM measures that maximize national net economic development benefits. This report documents the coastal storm water level and wave hazard, including sea level rise, for a variety of flood risk management alternatives. Four beach restoration alternatives for Galveston Island and Bolivar peninsula were evaluated. Suites of synt

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Borda, Patrice, and Allan Wright. Macroeconomic Fluctuations Under Natural Disaster Shocks in Central America and the Caribbean. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0011778.

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This paper examines the role of disaster shock in a one-sector, representative agent dynamic stochastic general equilibrium model (DSGE). First, it estimates a panel vector autoregresive (VAR) model for output, investment, trade balance, consumption, and country spread to capture the economic effects of output, country risk, and exogenous natural disaster shocks. The study determines the empirical dynamic responses of ten Caribbean countries and seven countries in Central America. Second, by taking into account rare events and trend shocks, this paper also provides a baseline framework of the

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Kim, Chang-Jin, and Jeremy M. Piger. Common Stochastic Trends, Common Cycles, and Asymmetry in Economic Fluctuations. Federal Reserve Bank of St. Louis, 2001. http://dx.doi.org/10.20955/wp.2001.014.

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Rotemberg, Julio, and Michael Woodford. Is the Business Cycles a Necessary Consequence of Stochastic Growth? National Bureau of Economic Research, 1994. http://dx.doi.org/10.3386/w4650.

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Rotemberg, Julio. Stochastic Technical Progress, Nearly Smooth Trends and Distinct Business Cycles. National Bureau of Economic Research, 2002. http://dx.doi.org/10.3386/w8919.

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Otrok, Christopher, Huigang Chen, Alessandro Rebucci, Gianluca Benigno, and Eric R. Young. Financial Crises and Macro-Prudential Policies. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0011201.

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Stochastic general equilibrium models of small open economies with occasionally binding financial frictions are capable of mimicking both the business cycles and the crisis events associated with the sudden stop in access to credit markets (Mendoza, 2010). This paper studies the inefficiencies associated with borrowing decisions in a two-sector small open production economy, finding that this economy is much more likely to display under-borrowing rather than over-borrowing in normal times. As a result, macro-prudential policies (e. g, Tobin taxes or economy-wide controls on capital inflows) ar

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Snyder, Victor A., Dani Or, Amos Hadas, and S. Assouline. Characterization of Post-Tillage Soil Fragmentation and Rejoining Affecting Soil Pore Space Evolution and Transport Properties. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580670.bard.

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Tillage modifies soil structure, altering conditions for plant growth and transport processes through the soil. However, the resulting loose structure is unstable and susceptible to collapse due to aggregate fragmentation during wetting and drying cycles, and coalescense of moist aggregates by internal capillary forces and external compactive stresses. Presently, limited understanding of these complex processes often leads to consideration of the soil plow layer as a static porous medium. With the purpose of filling some of this knowledge gap, the objectives of this Project were to: 1) Identif

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