Relevant bibliographies by topics / Stochastic modelling theory

Contents

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

Academic literature on the topic 'Stochastic modelling theory'

Author: Grafiati
Published: 19 February 2023
Last updated: 20 February 2023

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Journal articles on the topic "Stochastic modelling theory"

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Kołodziej, Joanna, William J. Knottenbelt, and Samee U. Khan. "Theory and Practice of Stochastic Modelling." Computers & Mathematics with Applications 64, no. 12 (December 2012): 3657. http://dx.doi.org/10.1016/j.camwa.2012.11.011.

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Fleishman, Benzion Semionovich. "Stochastic theory of community control." Ecological Modelling 39, no. 1-2 (November 1987): 121–59. http://dx.doi.org/10.1016/0304-3800(87)90017-2.

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Bertola, V., and E. Cafaro. "Deterministic–stochastic approach to compartment fire modelling." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 465, no. 2104 (December 9, 2008): 1029–41. http://dx.doi.org/10.1098/rspa.2008.0382.

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A generalized Semenov model is proposed to describe the dynamics of compartment fires. It is shown that the transitions to flashover or to extinction can be described in the context of the catastrophe theory (or the theory of dynamical systems) by introducing a suitable potential function of the smoke layer temperature. The effect on the fire dynamics of random perturbations is then studied by introducing a random noise term accounting for internal and external perturbations with an arbitrary degree of correlation. While purely Gaussian perturbations (white noise) do not change the behaviour of the fire with respect to the deterministic model, perturbations depending on the model variable (‘coloured’ noise) may drive the system to different states. This suggests that the compartment fires can be controlled or driven to extinction by introducing appropriate external perturbations.
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Frederiksen, Jorgen S., Terence J. O'Kane, and Meelis J. Zidikheri. "Subgrid modelling for geophysical flows." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1982 (January 13, 2013): 20120166. http://dx.doi.org/10.1098/rsta.2012.0166.

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Recently developed closure-based and stochastic model approaches to subgrid-scale modelling of eddy interactions are reviewed. It is shown how statistical dynamical closure models can be used to self-consistently calculate the eddy damping and stochastic backscatter parameters, required in large eddy simulations (LESs), from higher resolution simulations. A closely related direct stochastic modelling scheme that is more generally applicable to complex models is then described and applied to LESs of quasi-geostrophic turbulence of the atmosphere and oceans. The fundamental differences between atmospheric and oceanic LESs, which are related to the difference in the deformation scales in the two classes of flows, are discussed. It is noted that a stochastic approach may be crucial when baroclinic instability is inadequately resolved. Finally, inhomogeneous closure theory is applied to the complex problem of flow over topography; it is shown that it can be used to understand the successes and limitations of currently used heuristic schemes and to provide a basis for further developments in the future.
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Grum, Morten. "Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution." Water Science and Technology 37, no. 1 (January 1, 1998): 179–85. http://dx.doi.org/10.2166/wst.1998.0044.

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On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kalman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.
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Špaček, Miroslav. "Business Process Risk Modelling in Theory and Practice." Quality Innovation Prosperity 25, no. 1 (March 31, 2021): 55–72. http://dx.doi.org/10.12776/qip.v25i1.1551.

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Purpose: The purpose of the paper is to introduce SW based decision-making tool that helps managers cope with risks and uncertainties of selected industrial processes. The solution is substantiated by the theoretical background. Methodology/Approach: The research is based on combination of contextual interviews with process management experts and Business Process Modelling Notion (BPMN). The former is aimed at the identification of industrial processes with highest risk exposure the latter is conducive to the design of processes to be subjected to stochastic simulation. Findings: The findings show that the risks and uncertainties in the management of industrial processes can be kept under control when using advanced tools of risk analysis as simulation approaches. The solution proposed comes in handy to risk analysts or process managers. Research Limitation/Implication: The library of process models which were included into stochastic simulation includes selected processes as investments, service providing or economic value-added engineering. Additional processes are being included on ongoing basis. Originality/Value of paper: The paper offers the solution to industrial process risk management which goes far beyond academic sphere and provides industrial practitioners SW tool that facilitates process risk management.
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Amirdjanova, Anna. "Vortex theory approach to stochastic hydrodynamics." Mathematical and Computer Modelling 45, no. 11-12 (June 2007): 1319–41. http://dx.doi.org/10.1016/j.mcm.2006.11.001.

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Anastassiou, George A. "Multivariate stochastic Korovkin theory given quantitatively." Mathematical and Computer Modelling 48, no. 3-4 (August 2008): 558–80. http://dx.doi.org/10.1016/j.mcm.2007.04.022.

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Gulbinovič, Lech. "TECHNIQUES FOR MODELLING NETWORK SECURITY / KOMPIUTERIŲ SISTEMŲ SAUGUMO MODELIAVIMAS." Mokslas - Lietuvos ateitis 4, no. 1 (April 23, 2012): 27–30. http://dx.doi.org/10.3846/mla.2012.06.

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The article compares modelling techniques for network security, including the theory of probability, Markov processes, Petri networks and application of stochastic activity networks. The paper introduces the advantages and disadvantages of the above proposed methods and accepts the method of modelling the network of stochastic activity as one of the most relevant. The stochastic activity network allows modelling the behaviour of the dynamic system where the theory of probability is inappropriate. A real network distributes incidents referring to various distribution methods (exponential, gama, Veibul, etc.). A real system should evaluate time value when the stochastic activity network allows such activity. Santrauka Nagrinėjami šiuo metu žinomi kompiuterių sistemų saugumo modeliavimo metodai: tikimybių teorijos, Markovo procesų, Petri tinklų ir stochastinių veiklos tinklų. Šie metodai leidžia modeliuoti dinamines sistemas, kurioms kombinatoriniai metodai yra netinkami. Kadangi kompiuterių tinkluose įvykiai gali būti pasiskirstę ne tik pagal eksponentinį dėsnį, todėl jiems modeliuoti netinka Markovo procesų ir Petri tinklų modeliai. Realiuose tinkluose įvykiai gali būti pasiskirstę pagal eksponentinį, gama, Veibulo ir kt. dėsnius. Parodyta, kad iš aptartų šiuo metu žinomų modeliavimo metodų pagrindiniams saugumo veiksniams įvertinti tinkamiausias yra stochastinės veiklos tinklų metodas.
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Milz, Simon, Fattah Sakuldee, Felix A. Pollock, and Kavan Modi. "Kolmogorov extension theorem for (quantum) causal modelling and general probabilistic theories." Quantum 4 (April 20, 2020): 255. http://dx.doi.org/10.22331/q-2020-04-20-255.

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In classical physics, the Kolmogorov extension theorem lays the foundation for the theory of stochastic processes. It has been known for a long time that, in its original form, this theorem does not hold in quantum mechanics. More generally, it does not hold in any theory of stochastic processes -- classical, quantum or beyond -- that does not just describe passive observations, but allows for active interventions. Such processes form the basis of the study of causal modelling across the sciences, including in the quantum domain. To date, these frameworks have lacked a conceptual underpinning similar to that provided by Kolmogorov’s theorem for classical stochastic processes. We prove a generalized extension theorem that applies to all theories of stochastic processes, putting them on equally firm mathematical ground as their classical counterpart. Additionally, we show that quantum causal modelling and quantum stochastic processes are equivalent. This provides the correct framework for the description of experiments involving continuous control, which play a crucial role in the development of quantum technologies. Furthermore, we show that the original extension theorem follows from the generalized one in the correct limit, and elucidate how a comprehensive understanding of general stochastic processes allows one to unambiguously define the distinction between those that are classical and those that are quantum.
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Dissertations / Theses on the topic "Stochastic modelling theory"

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Li, Guangquan. "Stochastic modelling of carcinogenesis : theory and application." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486378.

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Cancer is a group of diseases characterized by autonomous, uncontrollable cell proliferation, evasion of cell death, self-construction of oxygen and nutrient supply and spreading of cancerous cells through metastasis. It is vital to elucidate pathways that underlie the cancer process. Mechanistic cancer models, to this extent, attempt to relate the occurrence: of malignant neoplasm to diverse risk factors such as genetic alterations, susceptibility of individuals and exogenous and endogenous carcinogenic exposures. The main objectives of this thesis are to examine the validity of the two-hit hypothesis for retinoblastoma (Knudson, 1971, PNAS (68) 820-23), to unify multiple types of genomic instability and to further assess the role of genomic instability played in the process of carcinogenesis. I shall also explore characteristics of existing mechanistic cancer models. This thesis begins with a survey' of basic cancer biology and existing mechanistic models. Utilizing a fully-stochastic two-stage clonal expansion model, the thesis specifically assesses the validity of the two-hit theory for retinoblastoma-(RB), a childhood ocular malignancy. Comparison of fits of a variety of models (in particular those with up to three mutations) to a population-based RB dfltaset demonstrates the superior fit of the two-stage model to others. This result strongly suggests both the necessity and sufficiency of the two RBI mutations to initiate RB and hence validates the two-hit theory. The thesis goes on to develop a comprehensive,. framework to incorporate multiple types of genomic instability, characterized by-numerous numerical and structural damages exhibiting in the cancer cell genome. This generalized model embraces���·;most, if not all, of the existing MVK-type models. Specific forms of the model are fitted to U.S. white American colon cancer incidence data. Based on comparison of fits to the population-based data, there is little evidence to support the hypothesis that models with more than one type of genomic instability fits better than those with a single type of genomic instability. Since the age-specific incidence data may not possess sufficient information for model discrimination, further investigation is required. The remainder ofthis thesis is concerned with two theoretical aspects. To facilitate a Bayesian implementation for data fitting, a flexible blocking algorithm is developed. In the presence of parameter correlation, the algorithm considerably improves the performance of the Markov chain Monte Carlo simulations. In addition, following a similar approach of Heidenreich et al. (1997, Risk Anal. (17) 391-399), the maximum number of identifiable parameters in the proposed cancer model WIth r types of genomIc InstabIlIty IS r +1 less than the number of biologically-based parameters.
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Zhao, Z. "Integration of neural and stochastic modelling techniques for speech recognition." Thesis, University of Essex, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305954.

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Malik, Sheheryar. "Essays in time series analysis : modelling stochastic volatility and forecast evaluation." Thesis, University of Warwick, 2009. http://wrap.warwick.ac.uk/2306/.

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Taleb, B. "The theory and design of a stochastic reliability simulator for large scale systems." Thesis, Open University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.383689.

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Hopf, Craig. "Exchange traded horserace betting fund with deterministic payoff – a mathematical analysis of a profitable deterministic horserace betting model." Thesis, Griffith University, 2014. http://hdl.handle.net/10072/366832.

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The horserace betting market is a subset of the financial market space, and wagering typically inherits a defined return – to – risk trade-off. For horserace betting input into institutional portfolio to be plausible, the payoff – to – risk trade-off from betting must be acceptable for the fund when compared with the return – risk trade-off from the existing mainstream assets included in portfolio investment. A new paradigm for horserace betting modelling and investing is acclaimed in this thesis, as premiss for betting input into institutional portfolio. An exchange traded betting fund is developed in the thesis that is able to generate pre-race (and within-race) investment arbitrage that offers an acceptable, defined return – risk trade-off for the risk averse investor. The extensive former horserace betting market stochastic modelling theory that forecasts racer expected outcomes and payoff, is today succeeded by this research that develops a deterministic horserace betting model (and algorithm) that generates defined payoff for the fund. This deterministic betting model challenges the existing semi-strong efficient market hypothesis toward horserace betting that no betting strategy consistently outperforms the financial market’s benchmark return. Subsequently, the primary research (alternative) hypothesis tested is H_a: profitable exchange traded horserace betting fund with deterministic payoff exists for acceptable institutional portfolio investment.
Thesis (Masters)
Master of Philosophy (MPhil)
Griffith School of Environment
Science, Environment, Engineering and Technology
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Shang, Xiaocheng. "Extended stochastic dynamics : theory, algorithms, and applications in multiscale modelling and data science." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20422.

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This thesis addresses the sampling problem in a high-dimensional space, i.e., the computation of averages with respect to a defined probability density that is a function of many variables. Such sampling problems arise in many application areas, including molecular dynamics, multiscale models, and Bayesian sampling techniques used in emerging machine learning applications. Of particular interest are thermostat techniques, in the setting of a stochastic-dynamical system, that preserve the canonical Gibbs ensemble defined by an exponentiated energy function. In this thesis we explore theory, algorithms, and numerous applications in this setting. We begin by comparing numerical methods for particle-based models. The class of methods considered includes dissipative particle dynamics (DPD) as well as a newly proposed stochastic pairwise Nosé-Hoover-Langevin (PNHL) method. Splitting methods are developed and studied in terms of their thermodynamic accuracy, two-point correlation functions, and convergence. When computational efficiency is measured by the ratio of thermodynamic accuracy to CPU time, we report significant advantages in simulation for the PNHL method compared to popular alternative schemes in the low-friction regime, without degradation of convergence rate. We propose a pairwise adaptive Langevin (PAdL) thermostat that fully captures the dynamics of DPD and thus can be directly applied in the setting of momentum-conserving simulation. These methods are potentially valuable for nonequilibrium simulation of physical systems. We again report substantial improvements in both equilibrium and nonequilibrium simulations compared to popular schemes in the literature. We also discuss the proper treatment of the Lees-Edwards boundary conditions, an essential part of modelling shear flow. We also study numerical methods for sampling probability measures in high dimension where the underlying model is only approximately identified with a gradient system. These methods are important in multiscale modelling and in the design of new machine learning algorithms for inference and parameterization for large datasets, challenges which are increasingly important in "big data" applications. In addition to providing a more comprehensive discussion of the foundations of these methods, we propose a new numerical method for the adaptive Langevin/stochastic gradient Nosé-Hoover thermostat that achieves a dramatic improvement in numerical efficiency over the most popular stochastic gradient methods reported in the literature. We demonstrate that the newly established method inherits a superconvergence property (fourth order convergence to the invariant measure for configurational quantities) recently demonstrated in the setting of Langevin dynamics. Furthermore, we propose a covariance-controlled adaptive Langevin (CCAdL) thermostat that can effectively dissipate parameter-dependent noise while maintaining a desired target distribution. The proposed method achieves a substantial speedup over popular alternative schemes for large-scale machine learning applications.
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Szekely, Tamas. "Stochastic modelling and simulation in cell biology." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:f9b8dbe6-d96d-414c-ac06-909cff639f8c.

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Modelling and simulation are essential to modern research in cell biology. This thesis follows a journey starting from the construction of new stochastic methods for discrete biochemical systems to using them to simulate a population of interacting haematopoietic stem cell lineages. The first part of this thesis is on discrete stochastic methods. We develop two new methods, the stochastic extrapolation framework and the Stochastic Bulirsch-Stoer methods. These are based on the Richardson extrapolation technique, which is widely used in ordinary differential equation solvers. We believed that it would also be useful in the stochastic regime, and this turned out to be true. The stochastic extrapolation framework is a scheme that admits any stochastic method with a fixed stepsize and known global error expansion. It can improve the weak order of the moments of these methods by cancelling the leading terms in the global error. Using numerical simulations, we demonstrate that this is the case up to second order, and postulate that this also follows for higher order. Our simulations show that extrapolation can greatly improve the accuracy of a numerical method. The Stochastic Bulirsch-Stoer method is another highly accurate stochastic solver. Furthermore, using numerical simulations we find that it is able to better retain its high accuracy for larger timesteps than competing methods, meaning it remains accurate even when simulation time is speeded up. This is a useful property for simulating the complex systems that researchers are often interested in today. The second part of the thesis is concerned with modelling a haematopoietic stem cell system, which consists of many interacting niche lineages. We use a vectorised tau-leap method to examine the differences between a deterministic and a stochastic model of the system, and investigate how coupling niche lineages affects the dynamics of the system at the homeostatic state as well as after a perturbation. We find that larger coupling allows the system to find the optimal steady state blood cell levels. In addition, when the perturbation is applied randomly to the entire system, larger coupling also results in smaller post-perturbation cell fluctuations compared to non-coupled cells. In brief, this thesis contains four main sets of contributions: two new high-accuracy discrete stochastic methods that have been numerically tested, an improvement that can be used with any leaping method that introduces vectorisation as well as how to use a common stepsize adapting scheme, and an investigation of the effects of coupling lineages in a heterogeneous population of haematopoietic stem cell niche lineages.
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Jin, Lei. "Particle systems and SPDEs with application to credit modelling." Thesis, University of Oxford, 2010. http://ora.ox.ac.uk/objects/uuid:07b29609-6941-4aa9-b4bc-29e7b4821b82.

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Wright, Gordon Gilbert. "An empirical analysis and stochastic modelling of aggregate demand behaviour in a spare parts inventory system." Thesis, City University London, 1991. http://openaccess.city.ac.uk/7728/.

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The focus of the work here was an empirical analysis of the aggregate independent demand behaviour for spare parts inventories, principally in the automotive industry. In particular, using the pioneering work of RG Brown (1959), who showed that inventory usage values are often log normally distributed, we set out and developed models that go some considerable way to explaining the underlying stochastic basis for this phenomena, why it occurs and some limiting conditions. The justification for this approach was on the grounds that by providing a more fundamental understanding of the underlying stochastic processes that explain the emergent aggregate demand behaviour, a sound starting point would be provided for developing more sophisticated analytical ways to view an inventory range, as a total entity, for planning and control purposes. The analysis was based on extensive data collected from the DAF Trucks (GB) Ltd. spare parts systems spanning the period 1975 to 1986, together with supporting studies from a number of other systems. The analysis showed that in the systems studied spare parts prices are lognormally distributed and this is most likely to be the result of a stochastic process known as the 'theory of breakage'. Analysis also showed that in the DAF Trucks case aggregated and volumes in very short time periods are distributed as a combined Log Series /Negative Binomial distribution (LSD/NBD). The combined LSD/NBD model of aggregate demand volumes is itself fully explained by a stochastic model known as the Afwedson model, which in turn is derived from more elementary conditions based on the Poisson process. We then demonstrated that if these short period aggregate demand distributions are cumulated period by period they converge to a log normal distribution as the stable long run model of aggregate demand volumes. As a result of the lognormality of prices and volumes the resultant inventory usage values are also log normal. Furthermore from insight into the underlying factors that explain the lognormality we have identified the factors and variables that govern the valueso f the parameterso f the particular log normal models of usage values. - The research protocol used in this work incorporated the law verifying process know as 'retroduction' after work and discussions of Uji Ijiri and Herbert Simon (1977); and to a lesser extent we utilised simulation for validation and verification of the derived models. From the proven log normality of demand volumes and usage values we have demonstrated that a number of related key inventory factors are also lognormal, in particular inventory- item turnover rates. Furthermore our conclusions show that some standard inventory performance measures, such as the inventory wide 'stock turnover rate' and the 'stock to sales' ratio, are poor measures to use in the case of highly skewed inventory variables. Finally we have suggested several potentially fruitful areas for developing improved methods of monitoring inventory performance in a variety of circumstances.
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Franz, Benjamin. "Recent modelling frameworks for systems of interacting particles." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:ac76d159-4cdd-40c9-b378-6ea1faf48aed.

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In this thesis we study three different modelling frameworks for biological systems of dispersal and combinations thereof. The three frameworks involved are individual-based models, group-level models in the form of partial differential equations (PDEs) and robot swarms. In the first two chapters of the thesis, we present ways of coupling individual based models with PDEs in so-called hybrid models, with the aim of achieving improved performance of simulations. Two classes of such hybrid models are discussed that allow an efficient simulation of multi-species systems of dispersal with reactions, but involve individual resolution for certain species and in certain parts of a computational domain if desired. We generally consider two types of example systems: bacterial chemotaxis and reaction-diffusion systems, and present results in the respective application area as well as general methods. The third chapter of this thesis introduces swarm robotic experiments as an additional tool to study systems of dispersal. In general, those experiments can be used to mimic animal behaviour and to study the impact of local interactions on the group-level dynamics. We concentrate on a target finding problem for groups of robots. We present how PDE descriptions can be adjusted to incorporate the finite turning times observed in the robotic system and that the adjusted models match well with experimental data. In the fourth and last chapter, we consider interactions between robots in the form of hard-sphere collisions and again derive adjusted PDE descriptions. We show that collisions have a significant impact on the speed with which the group spreads across a domain. Throughout these two chapters, we apply a combination of experiments, individual-based simulations and PDE descriptions to improve our understanding of interactions in systems of dispersal.
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Books on the topic "Stochastic modelling theory"

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B, Vinter R., ed. Stochastic modelling and control. London: Chapman and Hall, 1985.

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India) International Conference on Stochastic Modelling (2002 Cochin. Advances in stochastic modelling. Edited by Artalejo J. R, Krishnamoorthy A, and International Workshop on Retrial Queues (4th : 2002 : Cochin, India). Neshanic Station, NJ: Notable Publications, 2002.

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Wolff, Ronald W. Stochastic modelling and the theory of queues. London: Prentice-Hall, 1989.

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Desai, Uday B. Modelling and Application of Stochastic Processes. Boston, MA: Springer US, 1986.

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Wang, Hong. Bounded Dynamic Stochastic Systems: Modelling and Control. London: Springer London, 2000.

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Turbulence in fluids: Stochastic and numerical modelling. 2nd ed. Dordrecht: Kluwer Academic Publishers, 1990.

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Lesieur, Marcel. Turbulence in Fluids: Stochastic and numerical modelling. Dordrecht: Springer Netherlands, 1987.

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Turbulence in fluids: Stochastic and numerical modelling. Dordrecht: M. Nijhoff, 1987.

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Janssen, Jacques. Advances in Stochastic Modelling and Data Analysis. Dordrecht: Springer Netherlands, 1995.

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Tijms, Henk C. Stochastic Modeling and Analysis: A Computational Approach. Chichester, New York, USA: John Wiley & Sons Ltd., 1986.

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Book chapters on the topic "Stochastic modelling theory"

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Davis, M. H. A., and R. B. Vinter. "Filtering theory." In Stochastic Modelling and Control, 100–136. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4828-0_3.

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Davis, M. H. A., and R. B. Vinter. "Probability and linear system theory." In Stochastic Modelling and Control, 1–59. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-4828-0_1.

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Han, Te Sun. "Rate-Distortion Theory." In Stochastic Modelling and Applied Probability, 325–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-12066-8_5.

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Han, Te Sun. "Multi-Terminal Information Theory." In Stochastic Modelling and Applied Probability, 453–526. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-12066-8_7.

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Machiwal, Deepesh, and Madan Kumar Jha. "Stochastic Modelling of Time Series." In Hydrologic Time Series Analysis: Theory and Practice, 85–95. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-1861-6_5.

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Liptser, Robert S., and Albert N. Shiryaev. "Application of Optimal Nonlinear Filtering Equations to some Problems in Control Theory and Estimation Theory." In Stochastic Modelling and Applied Probability, 177–218. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-10028-8_6.

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Buldygin, Valeriĭ V., Karl-Heinz Indlekofer, Oleg I. Klesov, and Josef G. Steinebach. "Equivalence of Limit Theorems for Sums of Random Variables and Renewal Processes." In Probability Theory and Stochastic Modelling, 1–25. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99537-3_1.

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Buldygin, Valeriĭ V., Karl-Heinz Indlekofer, Oleg I. Klesov, and Josef G. Steinebach. "Asymptotics for Renewal Processes Constructed from Multi-indexed Random Walks." In Probability Theory and Stochastic Modelling, 395–417. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99537-3_10.

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Buldygin, Valeriĭ V., Karl-Heinz Indlekofer, Oleg I. Klesov, and Josef G. Steinebach. "Spitzer Series and Regularly Varying Functions." In Probability Theory and Stochastic Modelling, 419–38. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99537-3_11.

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Buldygin, Valeriĭ V., Karl-Heinz Indlekofer, Oleg I. Klesov, and Josef G. Steinebach. "Almost Sure Convergence of Renewal Processes." In Probability Theory and Stochastic Modelling, 27–52. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99537-3_2.

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Conference papers on the topic "Stochastic modelling theory"

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Raje, Shikhar, Navjyoti Singh, and Shobhit Mohan. "Modelling Evolving Voting Behaviour on Internet Platforms - Stochastic Modelling Approaches for Dynamic Voting Systems." In 8th International Conference on Evolutionary Computation Theory and Applications. SCITEPRESS - Science and Technology Publications, 2016. http://dx.doi.org/10.5220/0006073502390244.

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Yeomans, Julian Scott, and Raha Imanirad. "Modelling to generate alternatives in waste management facility expansion planning via simulation-optimization." In International Workshop of "Stochastic Programming for Implementation and Advanced Applications". The Association of Lithuanian Serials, 2012. http://dx.doi.org/10.5200/stoprog.2012.23.

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Public sector decision-making typically involves complex problems that are riddled with competing performance objectives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and there are frequently numerous stakeholders holding completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation optimization approach that combines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is demonstrated on a municipal sol- id waste management facility expansion case.
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Deye, Mohamed M. Ould, Mamadou Thiongane, and Mbaye Sene. "Modeling And Analyzing Cloud Auto-Scaling Mechanism Using Stochastic Well-Formed Coloured Nets." In 35th ECMS International Conference on Modelling and Simulation. ECMS, 2021. http://dx.doi.org/10.7148/2021-0253.

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Auto-scaling is one of the most important features in Cloud computing. This feature promises cloud computing customers the ability to best adapt the capacity of their systems to the load they are facing while maintaining the Quality of Service (QoS). This adaptation will be done automatically by increasing or decreasing the amount of resources being leveraged against the workload’s resource demands. There are two types and several techniques of auto-scaling proposed in the literature. However, regardless the type or technique of auto-scaling used, over-provisioning or under-provisioning problem is often observed. In this paper, we model the auto-scaling mechanism with the Stochastic Well-formed coloured Nets (SWN). The simulation of the SWN model allows us to find the state of the system (the number of requests to be dispatched, the idle times of the started resources) from which the auto-scaling mechanism must be operated in order to minimize the amount of used resources without violating the service-level agreements (SLA).
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Malara, Giovanni, Felice Arena, and Pol D. Spanos. "Dynamics and Hydrodynamics of a Moored Floating Rectangular Structure Under the Action of Random Sea Waves." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49486.

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This paper deals with the interaction of sea waves with a moored floating rectangular structure. The problem is of interest in various practical situations such as the design of floating breakwaters and of artificial islands, and the modelling of wave-ice sheet interaction. In the paper the incident wave field is modelled as a Gaussian stochastic process of a specified spectrum. In this context a diffraction problem and a radiation problem are posed. The related boundary value problem is discussed and solved by an eigen-functions expansion matching method. The method renders an estimate of the velocity potential at the first order in a Stokes’ expansion and, thus, of the wave pressure and of the wave forces. Several hydrodynamic quantities of interest are investigated. Specifically, reflection and transmission coefficients are derived and represented as a function of the structural dimensions. Further, the added mass and radiation damping terms are estimated. Then, the dynamics of the floating structure is examined by considering a 3-D-O-F system. Next, the wave-structure interaction is investigated in the context of a Quasi-Determinism theory. It is shown that the developed approach can be employed to account for both the dynamic and hydrodynamic effects of a structure in which diffraction is not negligible. The theoretical results are supplemented with data from pertinent Monte Carlo simulations.
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Herbert, Luke T., Zaza Hansen, and Peter Jacobsen. "SBAT: A Stochastic BPMN Analysis Tool." In ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/esda2014-20437.

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This paper presents SBAT, a tool framework for the modelling and analysis of complex business workflows. SBAT is applied to analyse an example from the Danish baked goods industry. Based upon the Business Process Modelling and Notation (BPMN) language for business process modelling, we describe a formalised variant of this language extended to support the addition of intention preserving stochastic branching and parameterised reward annotations. Building on previous work, we detail the design of SBAT, a software tool which allows for the analysis of BPMN models. Within SBAT, properties of interest are specified using the temporal logic Probabilistic Computation Tree Logic (PCTL) and we employ stochastic model checking, by means of the model checker PRISM, to compute their exact values. We present a simplified example of a distributed stochastic system where we determine a reachability property and the value of associated rewards in states of interest for a real-world example from a case company in the Danish baked goods industry. The developments are presented in a generalised fashion to make them relevant to the general problem of implementing quantitative probabilistic model checking of graph-based process modelling languages. This paper contains three key elements: 1. SBAT description. 2. Case company description. 3. Using SBAT on the case company. The paper concludes by indicating SBAT’s practical applicability and suggests further research directions.
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Kerekes, Gabriel, Jakob Raschhofer, Corinna Harmening, Hans Neuner, and Volker Schwieger. "Two-epoch TLS deformation analysis of a double curved wooden structure using approximating B-spline surfaces and fully-populated synthetic covariance matrices." In 5th Joint International Symposium on Deformation Monitoring. Valencia: Editorial de la Universitat Politècnica de València, 2022. http://dx.doi.org/10.4995/jisdm2022.2022.13816.

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This contribution presents a B-spline-based approach of area-wise deformation analysis applied on elements of a double curved wooden tower. The monitored object is the Urbach Tower with a height of 14 m. Terrestrial laser scans from two epochs acquired under real-world conditions are used for approximating two jointly parametrized B-spline surfaces of the tower’s outer shell. The stochastic model of the observations used within the surface approximation is based on elementary error theory and is defined by a synthetic variance-covariance matrix (SVCM). In addition to previous work on this topic, the object’s dimension is extended from a few dm to a few m and the measurement distance ranges from 20 to 60 m. Moreover, environment specific error sources are addressed in the SVCM, revealing the effect of the object’s dimension as well as of additional elementary errors on the estimated B-spline surfaces and the subsequent deformation analysis. Based on constructed points pairs using a grid of surface parameters, rigid body movements of the object under investigation are estimated while at the same time distorted regions of the wooden tower are detected. All results of the deformation analysis are statistically verified using hypothesis tests based on the elementary error model propagated through the processing algorithms of surface estimation and deformation analysis. The results demonstrate that during the modelling and deformation analysis, the measurement noise is reduced and therefore distorted regions are detectable in a statistically correct way.
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Pukl, Radomír, David Lehký, and Drahomír Novák. "Towards nonlinear reliability assessment of concrete transport structures." In IABSE Conference, Kuala Lumpur 2018: Engineering the Developing World. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2018. http://dx.doi.org/10.2749/kualalumpur.2018.0330.

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<p>Novel technique combining non-linear finite element analysis of the structural model with advanced stochastic simulation methods for realistic computer simulation and reliability assessment of civil engineering structures is presented. Elite non-linear material models are used for modelling of the structural materials within an advanced finite element computer simulation. Material properties and corresponding model parameters including their randomness and uncertainties are represented as random variables or random fields in the stochastic simulation using stratified Latin Hypercube Sampling and Simulated Annealing methods. Probabilistic evaluation of the numerical results enables to assess stochastic parameters of the model response, structural resistance, failure probability, safety index and structural reliability.</p>
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Steinbock, Gerhard, Troels Pedersen, Xuefeng Yin, and Bernard H. Fleury. "Experimental Characteristics of Indoor Wideband MIMO Radio Channels and their Impact on Stochastic Modelling." In 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop. IEEE, 2009. http://dx.doi.org/10.1109/dsp.2009.4785939.

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Selmair, Maximilian. "Taking randomness for granted: the complexities of applying random number streams in simulation modelling." In 36th ECMS International Conference on Modelling and Simulation. ECMS, 2022. http://dx.doi.org/10.7148/2022-0181.

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Uncertainty, as a constant companion of our world, is one major reason why simulation modelling takes precedence over static calculations to achieve accurate predictions. Computational random number generators are able to algorithmically determine values on the basis of random distributions, which utilise seed values to calculate streams of random numbers. This deterministic approach to replicating seemingly non-deterministic numbers ensures stochastic models to be reproducible at any time – one of the major requirements of simulation models. However, there are some pitfalls in the application of random number streams in modelling and simulation, which may even mislead experienced developers. In addition to a general introduction of the history of random number generators, this article shares empirical considerations and means by which the utilisation of random number streams can be improved to deliver valid and reliable results.
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Armstrong, Aaron, and Subha Kumpaty. "The Efficacy of Spreadsheet Modelling As an Alternative Means of Teaching Process Simulation." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11926.

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Abstract Spreadsheet based simulation has many advantages over the pre-programmed simulation applications more commonly used in teaching simulation in undergraduate courses. They are almost universally ubiquitous in business settings around the world. There is near certainty that students will have access to them after graduation since spreadsheets are a standard business tool used by nearly all engineers [1]. In addition, spreadsheets are already present within most standard operating systems. This means that there will be no need to buy or get approvals from Information Technology software committees or other managerial roadblocks. As an alternative to this, there are now free OpenOffice and LibreOffice spreadsheets available on most platforms which make their access effectively universal. Aside from their excellent availability, spreadsheets are an extremely capable learning tool for best practices in process simulation. Most engineering students are arriving at college with a good set of spreadsheet skills from their primary education and then the rest tend to pick it up early as underclassmen [2]. Spreadsheet simulation is easy to explain and generally very simple to debug. Although the now mainly antiquated code-based simulation packages used to offer these same advantages, they have now been largely replaced by more graphically oriented packages which depend in part on subtle mouse clicks and sometimes complex sub-menu structures. In addition, spreadsheets offer easily accessible native analysis and excellent graphing capabilities. Several advantages and potential disadvantages of spreadsheet simulation are presented in comparison to contemporary process simulation. Several simulation projects are then discussed related to Markovian processes including stochastic scatter patterns, sequential random object movement, multi-server queueing processes, dynamic intercept models, complex traffic and evacuation models, and Susceptible-Infected-Removed infections design simulations were taught using spreadsheet simulation.
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Reports on the topic "Stochastic modelling theory"

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Fleming, Wendell H., and Harold J. Kushner. Numerical Methods and Approximation and Modelling Problems in Stochastic Control Theory. Fort Belvoir, VA: Defense Technical Information Center, November 1988. http://dx.doi.org/10.21236/ada218419.

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