Relevant bibliographies by topics / Stochastic cycle

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Stochastic cycle'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Stochastic cycle"

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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 (June 13, 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 combustion. In this work, the joint use of unsteady Reynolds-averaged Navier–Stokes simulations for the analysis of the average engine cycle and the spark-ignition stochastic reactor model for the analysis of cycle-to-cycle variations is proposed. Thanks to the stochastic approach for the modeling of mixing and heat transfer, the spark-ignition stochastic reactor model can mimic the randomness of turbulent flows that is missing in the Reynolds-averaged Navier–Stokes modeling framework. The capability to predict cycle-to-cycle variations by the spark-ignition stochastic reactor model is extended by imposing two probability density functions. The probability density function for the scalar mixing time constant introduces a variation in the turbulent mixing time that is extracted from the unsteady Reynolds-averaged Navier–Stokes simulations and leads to variations in the overall mixing process. The probability density function for the inflammation time accounts for the delay or advancement of the early flame development. The combination of unsteady Reynolds-averaged Navier–Stokes and spark-ignition stochastic reactor model enables one to predict cycle-to-cycle variations using detailed chemistry in a fraction of computational time needed for a single large eddy simulation cycle.
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Brandenburg, Axel, and Gustavo Guerrero. "Cycles and cycle modulations." Proceedings of the International Astronomical Union 7, S286 (October 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 rather than the Coriolis force.
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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 (September 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 chaotization.
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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 (March 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 sensitivity of cycles. Using the stochastic sensitivity function (SSF) technique, we find a critical value of the parameter corresponding to the supersensitive cycle. For the neighborhood of this critical value, a comparative parametrical analysis of the phenomenon of the stochastic cycle splitting is performed. To predict the splitting bifurcation and estimate a threshold value of the noise intensity, we use a confidence domains method based on SSF. A phenomenon of the noise-induced chaotization is studied. We show that P-bifurcation of the splitting of stochastic cycles implies a D-bifurcation of a noise-induced chaotization.
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Melchionna, Andrew. "Stochastic sandpile on a cycle." Journal of Physics A: Mathematical and Theoretical 55, no. 19 (April 12, 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 to 1 sufficiently rapidly as n → ∞.
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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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BASHKIRTSEVA, I., L. RYASHKO, and P. STIKHIN. "NOISE-INDUCED BACKWARD BIFURCATIONS OF STOCHASTIC 3D-CYCLES." Fluctuation and Noise Letters 09, no. 01 (March 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 possibilities of this general method for the detailed BSB analysis of the multiple stochastic cycles of the forced Roessler system are demonstrated.
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SOWERS, RICHARD B. "STOCHASTIC AVERAGING NEAR LONG HETEROCLINIC ORBITS." Stochastics and Dynamics 07, no. 02 (June 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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Jia, Gaofeng, and Paolo Gardoni. "Stochastic life-cycle analysis: renewal-theory life-cycle analysis with state-dependent deterioration stochastic models." Structure and Infrastructure Engineering 15, no. 8 (March 27, 2019): 1001–14. http://dx.doi.org/10.1080/15732479.2019.1590424.

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Dissertations / Theses on the topic "Stochastic cycle"

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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 consequence of systems-level feedback rather than of proteolysis. This thesis applies mathematical modelling approaches to test this proposal for the Mto- G1 transition, which consists of two consecutive irreversible substeps: the metaphase-to-anaphase transition, and mitotic exit. The main objectives of the present work were: (i) to develop deterministic models to identify the essential molecular feedback loops and to examine their roles in the irreversibility of the M-to-G1 transition; (ii) to present a straightforward and reliable workflow to translate deterministic models of reaction networks into stochastic models; (iii) to explore the effects of noise on the cell cycle transitions using stochastic models, and to compare the deterministic and the stochastic approaches. In the first part of this thesis, I constructed a simplified deterministic model of the metaphase-to-anaphase transition, which is mainly regulated by the spindle assembly checkpoint (the SAC). Based on the essential feedback loops causing the bistability of the transition, this deterministic model provides explanations for three open questions regarding the SAC: Why is the SAC not reactivated when the kinetochore tension decreases to zero at anaphase onset? How can a single unattached kinetochore keep the SAC active? How is the synchronized and abrupt destruction of cohesin triggered? This deterministic model was then translated into a stochastic model of the SAC by treating the kinetochore microtubule attachment at prometaphase as a noisy process. The stochastic model was analyzed and simulation results were compared to the experimental data, with the aim of explaining the mitotic timing regulation by the SAC. Our model works remarkably well in qualitatively explaining experimental key findings and also makes testable predictions for different cell lines with very different number of chromosomes. The noise generated from the chemical interactions was found to only perturb the transit timing of the mitotic events, but not their ultimate outcomes: all cells eventually undergo anaphase, however, the time required to satisfy the SAC differs between cells due to stochastic effects. In the second part of the thesis, stochastic models of mitotic exit were created for two model organisms, budding yeast and mammalian cells. I analyzed the role of noise in mitotic exit at both the single-cell and the population level. Stochastic time series simulations of the models are able to explain the phenomenon of reversible mitotic exit, which is observed under specific experimental conditions in both model organisms. In spite of the fact that the detailed molecular networks of mitotic exit are very different in budding yeast and mammalian cells, their dynamic properties are similar. Importantly, bistability of the transitions is successfully captured also in the stochastic models. This work strongly supports the hypothesis that uni-directional cell cycle progression is a consequence of systems-level feedback in the cell cycle control system. Systems-level feedback creates alternative steady states, which allows cells to accomplish irreversible transitions, such as the M-to-G1 transition studied here. We demonstrate that stochastic models can serve as powerful tools to capture and study the heterogeneity of dynamical features among individual cells. In this way, stochastic simulations not only complement the deterministic approach, but also help to obtain a better understanding of mechanistic aspects. We argue that the effects of noise and the potential needs for stochastic simulations should not be overlooked in studying dynamic features of biological systems.
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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 maintenance and renewal decisions. Thus, a numerical model was developed and programmed using MATLAB which allows the quantification of the uncertainty in the LCC estimated for a given set of conditions. The model uses Monte Carlo simulation to determine the LCC associated with the installation, maintenance and renewal of the rail. The model incorporates imperfect inspections, a hazard function for rail fatigue defects modelled using the Weibull probability distribution and a P-F interval for rail fatigue defects modelled using an exponential probability distribution. The model also allows the modelling of maintenance as either perfect or minimal maintenance as well as the use of either flash butt or alumino-thermic welds to conduct the maintenance. This allowed the development of a method to assess which weld type to use to minimise the minimum attainable mean LCC. The developed model was validated against a similar stochastic rail maintenance model from the literature. However, the model from the literature considers only the expected LCC and does not show any uncertainty related thereto. The novelty in this study therefore lies in the fact that the LCC uncertainty can be quantified in the form of a probability distribution at any given renewal tonnage for a given set of conditions. It was found that the distribution of the LCC at a given renewal tonnage followed a lognormal probability distribution. The standard deviation of the lognormal distributions fitted using the method of maximum likelihood was used as a metric to quantify the uncertainty related to the life cycle cost at a given renewal tonnage. The LCC uncertainty was found to increase with an increase in inspection interval length. Furthermore, the uncertainty was also found to increase with a respective increase in renewal tonnage. For varying inspection interval lengths it was found that the uncertainty of combined maintenance costs (planned plus unplanned maintenance costs) tended more strongly towards the uncertainty in the planned maintenance costs for smaller inspection intervals and more strongly towards the uncertainty in unplanned maintenance costs for larger inspection intervals. A critical cost ratio was found of flash butt weld cost to alumino-thermic weld cost at which the minimum attainable mean LCC was equal. It is more economical to use flash butt welding for maintenance if the cost of flash butt welding maintenance produces a cost ratio lower than the critical cost ratio. The developed model could allow railway operators to assess the risk associated with renewal of the rail at varying renewal tonnages for given conditions such as inspection interval lengths, detectability of rail fatigue defects and the arrival rate of rail fatigue defects.
Dissertation (MEng)--University of Pretoria, 2017.
Civil Engineering
MEng
Unrestricted
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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 thèse, on s’intéresse au développement de modèles mathématiques de planification de production et de gestion de stock, quiprennent en compte ce phénomène d’incertitude sur la demande, essentiellement pour de produits à court cycle de vie. On proposeplusieurs modèles de planification de production, à petit horizon de planification, qui prennent en compte les différents aspects de notreproblématique, telles que la remise à jour des prévisions de la demande et les options de retour « Payback » des produits. On souligne,dans ces modèles, un aspect important qui prend de l’ampleur à cause de la mondialisation, et qui est lié à la différence entre les coûtsde production des différents fournisseurs. . On propose à la fin de la thèse, un modèle généralisé qui pourrait être appliqué à des produitsà long cycle de vie, et qui exploite quelques résultats obtenus pour les produits à court cycle de vie. Tous ces modèles sont résolusanalytiquement ou bien numériquement en utilisant la programmation dynamique stochastique
In the Supply Chain Management domain, the main source of randomness is the future demand. The influence of this demand variabilityon the performance of the Supply Chain is very important: for example, in 2007 the global inventory shortage rate in the retail industrywere around 8. 3%. On the other hand, in 2003 the global Unsaleable products cost around 1% in the grocery industry. These two types ofcosts, which are mainly caused by the uncertainty of the future demand, represent important lost for the whole Supply Chain actors. This Ph. D. Dissertation aims at developing mathematical production planning and inventory management models, which take intoconsideration the randomness of the future demand in order to reduce its economic negative impact, essentially for short life cycleproducts. We provide many planning models that consider the main issues of the planning problems, such as the production capacities,the information updating processes, the supply contracts and the advanced capacity reservation in a total costs minimization context. Weconsider in these models some aspects that are not considered in the literature, such as the “Payback” or the return options. Weemphasize also on an important issue that characterize the globalization of the industry, which may be resumed in the difference betweenthe procurement costs of the different suppliers. This issue is considered in the most chapters presenting models for short life cycleproducts and in the last chapter it is generalized to a long life cycle products setting. All the presented models are solved eitheranalytically or numerically using the dynamic stochastic programming
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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 investigated to illustrate the bipolar localization of the protein PopZ. However, stochastic simulations are often impeded by expensive computational cost for large and complex biochemical networks. The hybrid stochastic simulation algorithm is a combination of differential equations for traditional deterministic models and Gillespie's algorithm (SSA) for stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks with multiscale features, which contain both species populations and reaction rates with widely varying magnitude. The populations of some reactant species might be driven negative if they are involved in both deterministic and stochastic systems. This dissertation investigates the negativity problem of the hybrid method, proposes several remedies, and tests them with several models including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of empirical data must be large enough to obtain statistically valid parameter estimates. To optimize system parameters, a quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic budding yeast cell cycle model by matching multivariate probability distributions between simulated results and empirical data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental cooperative binding mechanism by a stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different objective functions are explored targeting different features of the empirical data.
Doctor of Philosophy
Modeling and simulation of biochemical networks faces numerous challenges as biochemical networks are discovered with increased complexity and unknown mechanisms. With 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, or numerical models based on probability distributions, for gene and protein networks at cellular levels that match well with the data and account for randomness. This dissertation studies a stochastic model in space and time of a bacterium’s life cycle— Caulobacter. A two-dimensional model based on a natural pattern mechanism is investigated to illustrate the changes in space and time of a key protein population. However, stochastic simulations are often complicated by the expensive computational cost for large and sophisticated biochemical networks. The hybrid stochastic simulation algorithm is a combination of traditional deterministic models, or analytical models with a single output for a given input, and stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks that contain both species populations and reaction rates with widely varying magnitude. The populations of some species may become negative in the simulation under some circumstances. This dissertation investigates negative population estimates from the hybrid method, proposes several remedies, and tests them with several cases including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of observed data must be large enough to obtain valid results. To optimize system parameters, the quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic (budding) yeast life cycle model by matching different distributions between simulated results and observed data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental molecular binding mechanism by the stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different optimization strategies are explored targeting different features of the observed data.
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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 several tuning parameter changes were made. Finally the precipitation from RegCM was split into 9 rainfall classifications which were then studied to determine how the regional climate model performed for representing rainfall events in the model, in terms of duration, intensity, and overall structure between all the event types.
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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 properties of South African macroeconomic data that may be used to estimate the parameters in these models. It includes a discussion of the variables that may be included in such a model, as well as various methods that may be used to extract the business cycle. Thereafter, the sample size for the dataset is established, after investigating for possible structural breaks in the rst two moments of the data, using various univariate and multivariate techniques. The nal chapter of this part contains an investigation into the measures of core in ation, whereby a comparison of trimmed means, dynamic factor models and various wavelet decompositions are applied to data for South Africa. The third part considers the application of the dataset that was identi ed in part two, in a DSGE model that incorporates features that are typical of small open economies. It includes a discussion that relates to the role of the exchange rate in these models, which is found to contain key information. In addition, this part also includes a optimal policy investigation, which considers the reaction function of central bank. The nal part of this thesis considers more recent advances that have been applied to DSGE models for the South African economy. It includes an example of a nonlinear model that is estimated with the aid of a particle lter, which is then used for forecasting purposes. The forecasting results of both linear and nonlinear versions of the model are then compared with the results from various Vector Autoregression (VAR) and Bayesian VAR models.
AFRIKAANSE OPSOMMING: Hierdie proefskrif oorweeg die gebruik van Dinamiese Stogastiese Algemene Ewewig (Engels: Dynamic Stochastic General Equilibrium (DSGE)) modelle vir die analise van besigheidsiklus gebeure in die Suid Afrikaanse makroekonomie. Dit bestaan uit vier aparte dog onderling verwante dele wat in « logiese ontwikkeling vorm. Die eerste deel motiveer die gebruik van dié modelle en daarna word die teoretiese onderbou van die modelle daargestel. Die teoretiese onderbou word aangevul met gedetaileerde stappe van die a eiding van die verhoudings wat gebruik word om « model vir « klein oop ekonomie saam te stel. Die tweede deel oorweeg die eienskappe van Suid Afrikaanse makroekonomiese data wat relevant is vir « ekonometriese model in hierdie konteks. Dit sluit « bespreking in van die veranderlikes wat vir so « model gebruik kan word, asook « bespreking van die verskeie metodes wat gebruik kan word om die besigheidsiklus uit die data te identi seer. Die steekproefgrootte van die data word dan vasgestel, ná die moontlikheid van strukturele onderbrekings van tendens in die eerste en tweede momente van die data ondersoek is met behulp van verskeie enkel en meervoudige-veranderlike tegnieke. Die laaste hoofstuk van dié deel is « studie van verskeie maatstawwe van kern in asie (core in ation), waar « vergelyking getref word tussen die resultate van die volgende metodes toegepas op Suid Afrikaanse data: afgesnede gemiddeldes (trimmed means), dinamiese faktor modelle en verskeie golfvormige onderverdelings (wavelet decompositions). Die derde deel gebruik die datastel, wat in deel twee ontwikkel is, in die passing van « DSGE model wat die tipiese eienskappe van « klein oop ekonomie inkorporeer. Dit sluit « bespreking in van die rol van die wisselkoers in hierdie tipe modelle, en daar word empiries bevind dat die wisselkoers belangrike inligting bevat. Hierdie deel sluit ook « ondersoek in van optimale beleid in terme van die reaksie funksie van die sentrale bank. Die laaste deel van die proefskrif bestudeer die resultate van onlangse ontwikkellinge in DSGE modelle wat toegepas word op die Suid Afrikaanse ekonomie. Dit sluit « voorbeeld van « nie-liniêre model wat met behulp van « partikel lter (particle lter) geskat word en gebruik word vir vooruitskattings. Die vooruitskattings uit beide die liniêre en nie-liniêre modelle word dan vergelyk met dié verkry uit verskeie Vektor
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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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We investigate the eff ect of aggregate uncertainty shocks on real variables. More speci fically, we introduce a shock in the volatility of productivity in an RBC model with long-run volatility risk and preferences that exhibit generalised disappointment aversion. We find that, when combined with a negative productivity shock, a volatility shock leads to further decline in real variables, such as output, consumption, hours worked and investment. For instance, out of the 2% decrease in output as a result of both shocks, we attribute 0.25% to the e ffect of an increase in volatility. We also fi nd that this e ffect is the same as the one obtained in a model with Epstein-Zin- Weil preferences, but higher than that of a model with expected utility. Moreover, GDA preferences yield superior asset pricing results, when compared to both Epstein-Zin-Weil preferences and expected utility.
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Books on the topic "Stochastic cycle"

1

Jonsson, Gunnar. Stochastic fiscal policy and the Swedish business cycle. Stockholm: 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: Bristol University, Department of Economics, 1992.

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Rotemberg, Julio. Is the business cycle a necessary consequence of stochastic growth? Cambridge, Mass: 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. Bristol: 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. Ogden, Utah: 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. Ogden, Utah (324 25th Street, Ogden 84401): 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. Ogden, Utah (324 25th Street, Ogden 84401): 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. Ogden, Utah: 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. Ogden, Utah (324 25th Street, Ogden 84401): 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. Reading, England: University of Reading, Dept. of Economics, 1992.

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Book chapters on the topic "Stochastic cycle"

1

Mura, Ivan. "Cell Cycle Modeling, Stochastic Methods." In Encyclopedia of Systems Biology, 294–96. New York, NY: 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, 201–19. New York, NY: 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, 28–46. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4757-3929-9_3.

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Yoshimura, Kazuyuki. "Phase Reduction of Stochastic Limit-Cycle Oscillators." In Reviews of Nonlinear Dynamics and Complexity, 59–90. Weinheim, Germany: 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, 253–73. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-2030-5_14.

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Gao, Haifeng, Enrico Zio, Anjenq Wang, and Guangchen Bai. "Low-Cycle Fatigue Damage Assessment of Turbine Blades Using a Substructure-Based Reliability Approach." In Stochastic Models in Reliability Engineering, 281–316. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429331527-19.

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Aulin, Arvid. "The Role of Stochastic Shocks in the Business Cycle." In Lecture Notes in Economics and Mathematical Systems, 172–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-95861-8_10.

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Kullig, E., H. Riesch-Oppermann, T. Winkler, and A. Brückner-Foit. "Lifetime prediction for thermal fatigue: development of a stochastic model." In Low Cycle Fatigue and Elasto-Plastic Behaviour of Materials—3, 829–34. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2860-5_131.

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Steck, E. "A Stochastic Model for the Interaction of Plasticity and Creep in Metals." In Low Cycle Fatigue and Elasto-Plastic Behaviour of Materials, 171–76. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3459-7_25.

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Jia, Gaofeng, and Paolo Gardoni. "Stochastic life-cycle analysis and performance optimization of deteriorating engineering systems using state-dependent deterioration stochastic models." In Routledge Handbook of Sustainable and Resilient Infrastructure, 580–602. Abingdon, Oxon ; New York, NY : Routledge, 2019. |: Routledge, 2018. http://dx.doi.org/10.4324/9781315142074-30.

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Conference papers on the topic "Stochastic cycle"

1

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. Singapore: 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. New York, New York, USA: 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. New York, New York, USA: 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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Maldonado, Bryan P., and Anna G. Stefanopoulou. "Non-Equiprobable Statistical Analysis of Misfires and Partial Burns for Cycle-to-Cycle Control of Combustion Variability." In ASME 2018 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icef2018-9540.

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Cycle-to-cycle combustion variability (CV) in spark ignition internal combustion engines is amplified at high levels of exhaust gas recirculation (EGR) by sporadic partial burn and misfire events. A non-equiprobable cycle classification method, based on the magnitude of the indicated mean effective pressure (IMEP), was developed to discern and study the deterministic and stochastic components of cyclic CV. The time series analysis of experimental combustion cycles suggested that the occurrence of high energy release cycles right after misfires is the only deterministic component between consecutive cycles. This predictable behavior results from the retained air and fuel from the incomplete combustion cycle to the next. On the other hand, this study shows that the occurrence of partial burn and misfire cycles is the product of the stochastic component of cyclic CV with statistical properties similar to a multinomial probability distribution. It is demonstrated that observation of partial burns can increase the probability of observing a misfire when the conditional probability is used as the metric. Based on these findings, future work will be able to use the observation of partial burns alone to control the upper bound on the probability of misfire events. To this end, different metrics are proposed to control directly and indirectly the probability of misfires, and their advantages and disadvantages for feedback combustion control are discussed.
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Gao, F., and G. B. Sheble. "Stochastic Optimization Techniques for Economic Dispatch with Combined Cycle Units." In 2006 International Conference on Probabilistic Methods Applied to Power Systems. IEEE, 2006. http://dx.doi.org/10.1109/pmaps.2006.360244.

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Mavris, Dimitri N., Daniel A. DeLaurentis, Mark A. Hale, and Jimmy C. M. Tai. "Elements of an Emerging Virtual Stochastic Life Cycle Design Environment." In World Aviation Congress & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1999. http://dx.doi.org/10.4271/1999-01-5638.

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Li, Yao, Cesar Augusto Vargas-Garcia, and Abhyudai Singh. "Stochastic stability of a cell cycle model with "silence period"." In 2020 European Control Conference (ECC). IEEE, 2020. http://dx.doi.org/10.23919/ecc51009.2020.9143745.

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Mishra, Chinmaya, and P. M. V. Subbarao. "Stochastic Cycle to Cycle Prediction in a Reactivity Controlled Compression Ignition Engine Using Double Wiebe Function." In SAE WCX Digital Summit. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2021. http://dx.doi.org/10.4271/2021-01-0374.

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Reports on the topic "Stochastic cycle"

1

Melby, Jeffrey, Thomas Massey, Fatima Diop, Himangshu Das, Norberto Nadal-Caraballo, Victor Gonzalez, Mary Bryant, 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.), July 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 synthetic tropical and historical non-tropical storms were developed and modeled. The CSTORM coupled surge-and-wave modeling system was used to accurately characterize storm circulation, water level, and wave hazards using new model meshes developed from high-resolution land and sub-aqueous surveys for with- and without-project scenarios. Beach morphology stochastic response was modeled with a Monte Carlo life-cycle simulation approach using the CSHORE morphological evolution numerical model embedded in the StormSim stochastic modeling system. Morphological and hydrodynamic response were primarily characterized with probability distributions of the number of rehabilitations and overflow.
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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? Cambridge, MA: National Bureau of Economic Research, February 1994. http://dx.doi.org/10.3386/w4650.

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

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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, April 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) Identify and quantify the major factors causing breakdown of primary soil fragments produced by tillage into smaller secondary fragments; 2) Identify and quantify the. physical processes involved in the coalescence of primary and secondary fragments and surfaces of weakness; 3) Measure temporal changes in pore-size distributions and hydraulic properties of reconstructed aggregate beds as a function of specified initial conditions and wetting/drying events; and 4) Construct a process-based model of post-tillage changes in soil structural and hydraulic properties of the plow layer and validate it against field experiments. A dynamic theory of capillary-driven plastic deformation of adjoining aggregates was developed, where instantaneous rate of change in geometry of aggregates and inter-aggregate pores was related to current geometry of the solid-gas-liquid system and measured soil rheological functions. The theory and supporting data showed that consolidation of aggregate beds is largely an event-driven process, restricted to a fairly narrow range of soil water contents where capillary suction is great enough to generate coalescence but where soil mechanical strength is still low enough to allow plastic deforn1ation of aggregates. The theory was also used to explain effects of transient external loading on compaction of aggregate beds. A stochastic forInalism was developed for modeling soil pore space evolution, based on the Fokker Planck equation (FPE). Analytical solutions for the FPE were developed, with parameters which can be measured empirically or related to the mechanistic aggregate deformation model. Pre-existing results from field experiments were used to illustrate how the FPE formalism can be applied to field data. Fragmentation of soil clods after tillage was observed to be an event-driven (as opposed to continuous) process that occurred only during wetting, and only as clods approached the saturation point. The major mechanism of fragmentation of large aggregates seemed to be differential soil swelling behind the wetting front. Aggregate "explosion" due to air entrapment seemed limited to small aggregates wetted simultaneously over their entire surface. Breakdown of large aggregates from 11 clay soils during successive wetting and drying cycles produced fragment size distributions which differed primarily by a scale factor l (essentially equivalent to the Van Bavel mean weight diameter), so that evolution of fragment size distributions could be modeled in terms of changes in l. For a given number of wetting and drying cycles, l decreased systematically with increasing plasticity index. When air-dry soil clods were slightly weakened by a single wetting event, and then allowed to "age" for six weeks at constant high water content, drop-shatter resistance in aged relative to non-aged clods was found to increase in proportion to plasticity index. This seemed consistent with the rheological model, which predicts faster plastic coalescence around small voids and sharp cracks (with resulting soil strengthening) in soils with low resistance to plastic yield and flow. A new theory of crack growth in "idealized" elastoplastic materials was formulated, with potential application to soil fracture phenomena. The theory was preliminarily (and successfully) tested using carbon steel, a ductile material which closely approximates ideal elastoplastic behavior, and for which the necessary fracture data existed in the literature.
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