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Journal articles on the topic 'Stochastic'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Engelbert, H. J., and V. P. Kurenok. "On Multidimensional SDEs Without Drift and with A Time-Dependent Diffusion Matrix." Georgian Mathematical Journal 7, no. 4 (2000): 643–64. http://dx.doi.org/10.1515/gmj.2000.643.

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Abstract We study multidimensional stochastic equations where x o is an arbitrary initial state, W is a d-dimensional Wiener process and is a measurable diffusion coefficient. We give sufficient conditions for the existence of weak solutions. Our main result generalizes some results obtained by A. Rozkosz and L. Słomiński [Stochastics Stochasties Rep. 42: 199–208, 1993] and T. Senf [Stochastics Stochastics Rep. 43: 199–220, 1993] for the existence of weak solutions of one-dimensional stochastic equations and also some results by A. Rozkosz and L. Słomiński [Stochastic Process. Appl. 37: 187–19

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2

Luo, Mei-Ju, and Yuan Lu. "Properties of Expected Residual Minimization Model for a Class of Stochastic Complementarity Problems." Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/497586.

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Expected residual minimization (ERM) model which minimizes an expected residual function defined by an NCP function has been studied in the literature for solving stochastic complementarity problems. In this paper, we first give the definitions of stochasticP-function, stochasticP0-function, and stochastic uniformlyP-function. Furthermore, the conditions such that the function is a stochasticPP0-function are considered. We then study the boundedness of solution set and global error bounds of the expected residual functions defined by the “Fischer-Burmeister” (FB) function and “min” function. T

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3

IMKELLER, PETER, and ADAM HUGH MONAHAN. "CONCEPTUAL STOCHASTIC CLIMATE MODELS." Stochastics and Dynamics 02, no. 03 (2002): 311–26. http://dx.doi.org/10.1142/s0219493702000443.

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From July 9 to 11, 2001, 50 researchers from the fields of climate dynamics and stochastic analysis met in Chorin, Germany, to discuss the idea of stochastic models of climate. The present issue of Stochastics and Dynamics collects several papers from this meeting. In this introduction to the volume, the idea of simple conceptual stochastic climate models is introduced amd recent results in the mathematically rigorous development and analysis of such models are reviewed. As well, a brief overview of the application of ideas from stochastic dynamics to simple models of the climate system is giv

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4

Liu, Caixia, Yingqi Zhang, and Huixia Sun. "Finite-TimeH∞Filtering for Singular Stochastic Systems." Journal of Applied Mathematics 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/615790.

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This paper addresses the problem of finite-timeH∞filtering for one family of singular stochastic systems with parametric uncertainties and time-varying norm-bounded disturbance. Initially, the definitions of singular stochastic finite-time boundedness and singular stochasticH∞finite-time boundedness are presented. Then, theH∞filtering is designed for the class of singular stochastic systems with or without uncertain parameters to ensure singular stochastic finite-time boundedness of the filtering error system and satisfy a prescribedH∞performance level in some given finite-time interval. Furth

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5

LIUM, ARNT-GUNNAR, TEODOR GABRIEL CRAINIC, and STEIN W. WALLACE. "CORRELATIONS IN STOCHASTIC PROGRAMMING: A CASE FROM STOCHASTIC SERVICE NETWORK DESIGN." Asia-Pacific Journal of Operational Research 24, no. 02 (2007): 161–79. http://dx.doi.org/10.1142/s0217595907001206.

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Deterministic models, even if used repeatedly, will not capture the essence of planning in an uncertain world. Flexibility and robustness can only be properly valued in models that use stochastics explicitly, such as stochastic optimization models. However, it may also be very important to capture how the random phenomena are related to one another. In this article we show how the solution to a stochastic service network design model depends heavily on the correlation structure among the random demands. The major goal of this paper is to discuss why this happens, and to provide insights into t

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6

Zhang, Yingqi, Wei Cheng, Xiaowu Mu та Caixia Liu. "Stochasticℋ∞Finite-Time Control of Discrete-Time Systems with Packet Loss". Mathematical Problems in Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/897481.

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This paper investigates the stochastic finite-time stabilization andℋ∞control problem for one family of linear discrete-time systems over networks with packet loss, parametric uncertainties, and time-varying norm-bounded disturbance. Firstly, the dynamic model description studied is given, which, if the packet dropout is assumed to be a discrete-time homogenous Markov process, the class of discrete-time linear systems with packet loss can be regarded as Markovian jump systems. Based on Lyapunov function approach, sufficient conditions are established for the resulting closed-loop discrete-time

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7

Polyakova, A. Yu. "Feat ures of continuing formati on of stochastic cult ure of schoolchildren in the conditions of dista nce learning." Informatics in school, no. 6 (September 25, 2021): 39–48. http://dx.doi.org/10.32517/2221-1993-2021-20-6-39-48.

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The article describes the essence of continuity in the formation of a stochastic culture of students in the conditions of distance learning. The author’s definition of the concept “continuity in the formation of stochastic culture of students of a general education school in the conditions of distance learning” is given. There are the basic conditions of a teacher’s possession of the highest level of stochastic culture, due to which the formation of an integral personal quality, which is a generalized indicator of stochastic competence, takes place in schoolchildren. Modern information and com

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8

Sankar, T. S., S. A. Ramu, and R. Ganesan. "Stochastic Finite Element Analysis for High Speed Rotors." Journal of Vibration and Acoustics 115, no. 1 (1993): 59–64. http://dx.doi.org/10.1115/1.2930315.

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The general problem of the dynamic response of highspeed rotors is considered in which certain system parameters may have a spatial stochastic variation. In particular the elastic modulus and mass density of a rotating shaft are described through one dimensional stochastic field functions so that the imperfections in manufacture and measurement can be accounted for. The stochastic finite element method is developed so that the variability of the response of the rotor can be interpreted in terms of the variation of the material property. As an illustration the whirl speed analysis is performed

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9

Hu, Peng, та Chengming Huang. "The StochasticΘ-Method for Nonlinear Stochastic Volterra Integro-Differential Equations". Abstract and Applied Analysis 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/583930.

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The stochasticΘ-method is extended to solve nonlinear stochastic Volterra integro-differential equations. The mean-square convergence and asymptotic stability of the method are studied. First, we prove that the stochasticΘ-method is convergent of order1/2in mean-square sense for such equations. Then, a sufficient condition for mean-square exponential stability of the true solution is given. Under this condition, it is shown that the stochasticΘ-method is mean-square asymptotically stable for every stepsize if1/2≤θ≤1and when0≤θ<1/2, the stochasticΘ-method is mean-square asymptotically stable

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10

Lykova, K. G. "METHODOLOGY OF FORMING A STOCHASTIC WORLDVIEW WHILE STUDYING THE SECTION "RANDOM EVENTS. VEROBILITIES"." Educational Psychology in Polycultural Space 56, no. 4 (2021): 67–77. http://dx.doi.org/10.24888/2073-8439-2021-56-4-67-77.

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The article contains general provisions, characterizing the methodology of forming stochastic worldview of high school students. The methodology is carried out in accordance with the developed worldview significant educational material, accompanied by the support of specially selected digital technology, and in accordance with the main stages of the formation of worldview while teaching mathematics. The main stages of the implementation of the holistic process of learning stochasticity are: preparatory, problem-research, implementation and correctional. It is supposed that the methodology of f

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11

Gozzi, Ennio. "Stochastic and Non-Stochastic Supersymmetry." Progress of Theoretical Physics Supplement 111 (1993): 115–50. http://dx.doi.org/10.1143/ptps.111.115.

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12

Anishchenko, Vadim, and Aleksander Neiman. "Stochastic resonance and stochastic synchronization." Izvestiya VUZ. Applied Nonlinear Dynamics 5, no. 1 (1997): 5–14. http://dx.doi.org/10.18500/0869-6632-1997-5-1-5-14.

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The fundamental phenomenon of synchronization occurs in non-lirear self—sustained oscillators subjecled to а periodic force or coupled with each other. This phenomenon manifests itself in locking or suppressing of the natural frequency of the oscillator by periodic force. In this paper we discuss surprising synchronization like phenomena in stochastic bistable systems which have no natural frequency at all. A stochastic bistable system possesses а noise—controlled mean switching frequeicy between metastable states being ап analogy of the natural frequency. The stochastic synchronization reveal

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13

Veraart, Almut E. D., and Luitgard A. M. Veraart. "Stochastic volatility and stochastic leverage." Annals of Finance 8, no. 2-3 (2010): 205–33. http://dx.doi.org/10.1007/s10436-010-0157-3.

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14

TRIPŞA, Florența-Violeta, and Ana-Maria LUCA (RȊTEA). "STOCHASTIC APPROXIMATION FOR RELIABILITY PROBLEMS." SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, no. 1 (2016): 497–500. http://dx.doi.org/10.19062/2247-3173.2016.18.1.68.

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15

Sihotang, Hengki Tamando, Syahril Efendi, Muhammad Zarlis, and Herman Mawengkang. "Data driven approach for stochastic data envelopment analysis." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1497–504. http://dx.doi.org/10.11591/eei.v11i3.3660.

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Decision making based on data driven deals with a large amount of data will evaluate the process's effectiveness. Evaluate effectiveness in this paper is measure of performance efficiency of data envelopment analysis (DEA) method in this study is the approach with uncertainty problems. This study proposed a new method called the robust stochastic DEA (RSDEA) to approach performance efficiency in tackling uncertainty problems (i.e., stochastic and robust optimization). The RSDEA method develops to combine the stochastics DEA (SDEA) formulation method and Robust Optimization. The numerical examp

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16

Hengki, Tamando Sihotang, Efendi Syahril, Zarlis Muhammad, and Mawengkang Herman. "Data driven approach for stochastic data envelopment analysis." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1497~1504. https://doi.org/10.11591/eei.v11i3.3660.

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Decision making based on data driven deals with a large amount of data will evaluate the process's effectiveness. Evaluate effectiveness in this paper is measure of performance efficiency of data envelopment analysis (DEA) method in this study is the approach with uncertainty problems. This study proposed a new method called the robust stochastic DEA (RSDEA) to approach performance efficiency in tackling uncertainty problems (i.e., stochastic and robust optimization). The RSDEA method develops to combine the stochastics DEA (SDEA) formulation method and Robust Optimization. The numerical e

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17

Zhao, Wenqiang, and Yangrong Li. "Existence of Random Attractors for ap-Laplacian-Type Equation with Additive Noise." Abstract and Applied Analysis 2011 (2011): 1–21. http://dx.doi.org/10.1155/2011/616451.

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We first establish the existence and uniqueness of a solution for a stochasticp-Laplacian-type equation with additive white noise and show that the unique solution generates a stochastic dynamical system. By using the Dirichlet forms of Laplacian and an approximation procedure, the nonlinear obstacle, arising from the additive noise is overcome when we make energy estimate. Then, we obtain a random attractor for this stochastic dynamical system. Finally, under a restrictive assumption on the monotonicity coefficient, we find that the random attractor consists of a single point, and therefore t

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18

Petuhov, Sergey. "MUSIC, UNIVERSALS OF GENOMIC DNAs, GENETIC INTELLIGENCE, AND THE CONCEPT OF A STOCHASTIC SYSTEM OF PROTOREGULATION." Medicine and Art 1, no. 2 (2023): 40–57. http://dx.doi.org/10.60042/2949-2165-2023-1-2-40-57.

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This work is devoted to the structural links between the musical harmony of the Pythagorean fifth scales and the system of hydrogen bonds in genetic molecules DNAs. Hidden regularities in the stochastic organization of hydrogen bond sequences in the genomic DNAs of higher and lower organisms have been discovered. The regularities described are candidates for the role of universal regularities of biological evolution. An idea is advanced on the fundamental role of stochastic regularities in the genetically inherited organization of biological bodies. In the presented study, the author's method

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19

Sun, Huiying, Meng Li, Shenglin Ji, and Long Yan. "Stability and Linear Quadratic Differential Games of Discrete-Time Markovian Jump Linear Systems with State-Dependent Noise." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/265621.

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We mainly consider the stability of discrete-time Markovian jump linear systems with state-dependent noise as well as its linear quadratic (LQ) differential games. A necessary and sufficient condition involved with the connection between stochasticTn-stability of Markovian jump linear systems with state-dependent noise and Lyapunov equation is proposed. And using the theory of stochasticTn-stability, we give the optimal strategies and the optimal cost values for infinite horizon LQ stochastic differential games. It is demonstrated that the solutions of infinite horizon LQ stochastic differenti

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20

MTW and H. Kunita. "Stochastic Flows and Stochastic Differential Equations." Journal of the American Statistical Association 93, no. 443 (1998): 1251. http://dx.doi.org/10.2307/2669903.

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21

Krylov, Nicolai. "Stochastic flows and stochastic differential equations." Stochastics and Stochastic Reports 51, no. 1-2 (1994): 155–58. http://dx.doi.org/10.1080/17442509408833949.

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22

Bayraktar, Erhan, and Jiaqi Li. "Stochastic Perron for stochastic target games." Annals of Applied Probability 26, no. 2 (2016): 1082–110. http://dx.doi.org/10.1214/15-aap1112.

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23

Jacka, S. D., and H. Kunita. "Stochastic Flows and Stochastic Differential Equations." Journal of the Royal Statistical Society. Series A (Statistics in Society) 155, no. 1 (1992): 175. http://dx.doi.org/10.2307/2982680.

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24

De Falco, Diego. "Lévy's stochastic area in stochastic mechanics." Letters in Mathematical Physics 14, no. 1 (1987): 41–45. http://dx.doi.org/10.1007/bf00403468.

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25

Birge, John R., and M. A. H. Dempstert. "Stochastic programming approaches to stochastic scheduling." Journal of Global Optimization 9, no. 3-4 (1996): 417–51. http://dx.doi.org/10.1007/bf00121682.

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26

Bayraktar, Erhan, and Jiaqi Li. "Stochastic Perron for Stochastic Target Problems." Journal of Optimization Theory and Applications 170, no. 3 (2016): 1026–54. http://dx.doi.org/10.1007/s10957-016-0958-2.

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27

Hu, Wei. "Stochastic Finite-Time Stability for Stochastic Nonlinear Systems with Stochastic Impulses." Symmetry 14, no. 4 (2022): 817. http://dx.doi.org/10.3390/sym14040817.

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In this paper, some novel stochastic finite-time stability criteria for stochastic nonlinear systems with stochastic impulse effects are established. The results in this paper blackgeneralized the related results in from two aspects: 1. the model in is the deterministic systems, which means that the noise effect that can be described as a symmetric Markov process Brownian motion is considered in our models; 2. the stochastic finite-time stability criterion is established in this paper, not the asymptotic stability and the input-to-state stability that are studied in the form literature. Finall

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28

Field, R. V., M. Grigoriu, and J. M. Emery. "On the efficacy of stochastic collocation, stochastic Galerkin, and stochastic reduced order models for solving stochastic problems." Probabilistic Engineering Mechanics 41 (July 2015): 60–72. http://dx.doi.org/10.1016/j.probengmech.2015.05.002.

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29

Ovchinnikov, Igor V., Wenyuan Li, Yuquan Sun, et al. "Criticality or Supersymmetry Breaking?" Symmetry 12, no. 5 (2020): 805. http://dx.doi.org/10.3390/sym12050805.

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In many stochastic dynamical systems, ordinary chaotic behavior is preceded by a full-dimensional phase that exhibits 1/f-type power spectra and/or scale-free statistics of (anti)instantons such as neuroavalanches, earthquakes, etc. In contrast with the phenomenological concept of self-organized criticality, the recently found approximation-free supersymmetric theory of stochastics (STS) identifies this phase as the noise-induced chaos (N-phase), i.e., the phase where the topological supersymmetry pertaining to all stochastic dynamical systems is broken spontaneously by the condensation of the

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30

Johansyah, Muhamad Deni, Endang Rusyaman, Bob Foster, Khoirunnisa Rohadatul Aisy Muslihin, and Asep K. Supriatna. "Combining Differential Equations with Stochastic for Economic Growth Models in Indonesia: A Comprehensive Literature Review." Mathematics 12, no. 20 (2024): 3219. http://dx.doi.org/10.3390/math12203219.

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Economic growth modeling is one of the methods a government can use to formulate appropriate economic policies to improve the prosperity of its people. Differential equations and stochastic models play a major role in studying economic growth. This article aims to conduct a literature review on the use of differential equations in relation to stochastics to model economic growth. In addition, this article also discusses the use of differential and stochastic equations in economic growth models in Indonesia. This study involves searching for and selecting articles to obtain a collection of rese

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31

Vrkoč, Ivo. "Weak averaging of stochastic evolution equations." Mathematica Bohemica 120, no. 1 (1995): 91–111. http://dx.doi.org/10.21136/mb.1995.125891.

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32

Březková, L., M. Starý, and P. Doležal. "The real-time stochastic flow forecast." Soil and Water Research 5, No. 2 (2010): 49–57. http://dx.doi.org/10.17221/13/2009-swr.

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In the Czech Republic, deterministic flow forecasts with the lead time of 48 hours, calculated by rainfall-runoff models for basins of a size of several hundreds to thousands square kilometers, are nowadays a common part of the operational hydrological service. The Czech Hydrometeorological Institute (CHMI) issues daily the discharge forecast for more than one hundred river profiles. However, the causal rainfall is a random process more than a deterministic one, therefore the deterministic discharge forecast based on one precipitation prediction is a significant simplification of the reality.

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33

Budoor, Mohammed Abdelati*1 &. Entisar Alrasheedi2. "STUDY ON THE SOLUTION OF THE STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 7, no. 1 (2020): 17–20. https://doi.org/10.5281/zenodo.3600213.

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The main objective of this paper is to study the viscosity technical to solve stochastic partial differential equations(SPDEs) and to discuss the uniqueness of the stochastic viscosity solution and also to study a comparison theorem between a stochastic viscosity solution and an -wise stochastic viscosity solution.

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34

Yang, Hua, та Feng Jiang. "Stochasticθ-Methods for a Class of Jump-Diffusion Stochastic Pantograph Equations with Random Magnitude". Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/589167.

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This paper is concerned with the convergence of stochasticθ-methods for stochastic pantograph equations with Poisson-driven jumps of random magnitude. The strong order of the convergence of the numerical method is given, and the convergence of the numerical method is obtained. Some earlier results are generalized and improved.

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35

Leemans, Sander J. J., Wil M. P. van der Aalst, Tobias Brockhoff, and Artem Polyvyanyy. "Stochastic process mining: Earth movers’ stochastic conformance." Information Systems 102 (December 2021): 101724. http://dx.doi.org/10.1016/j.is.2021.101724.

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36

Arvanitis, Stelios. "Stochastic dominance efficient sets and stochastic spanning." Decisions in Economics and Finance 44, no. 1 (2021): 401–9. http://dx.doi.org/10.1007/s10203-021-00325-y.

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37

Lu, Xiang, Gunter Meissner, and Hong Sherwin. "A Unified Stochastic Volatility—Stochastic Correlation Model." Journal of Mathematical Finance 10, no. 04 (2020): 679–96. http://dx.doi.org/10.4236/jmf.2020.104039.

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38

Ohzeki, Masayuki. "Stochastic gradient method with accelerated stochastic dynamics." Journal of Physics: Conference Series 699 (March 2016): 012019. http://dx.doi.org/10.1088/1742-6596/699/1/012019.

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39

Klimontovich, Yu L. "What are stochastic filtering and stochastic resonance?" Uspekhi Fizicheskih Nauk 169, no. 1 (1999): 39. http://dx.doi.org/10.3367/ufnr.0169.199901d.0039.

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40

Ai, Bao-quan, and Liang-gang Liu. "Stochastic resonance in a stochastic bistable system." Journal of Statistical Mechanics: Theory and Experiment 2007, no. 02 (2007): P02019. http://dx.doi.org/10.1088/1742-5468/2007/02/p02019.

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41

Klimontovich, Yu L. "What are stochastic filtering and stochastic resonance?" Physics-Uspekhi 42, no. 1 (1999): 37–44. http://dx.doi.org/10.1070/pu1999v042n01abeh000445.

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42

Rice, Sean H., and Anthony Papadopoulos. "Evolution with Stochastic Fitness and Stochastic Migration." PLoS ONE 4, no. 10 (2009): e7130. http://dx.doi.org/10.1371/journal.pone.0007130.

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43

Kisielewicz, Michal. "Set-valued stochastic intergrals and stochastic inclutions1." Stochastic Analysis and Applications 15, no. 5 (1997): 783–800. http://dx.doi.org/10.1080/07362999708809507.

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44

Nemirovski, A., A. Juditsky, G. Lan, and A. Shapiro. "Robust Stochastic Approximation Approach to Stochastic Programming." SIAM Journal on Optimization 19, no. 4 (2009): 1574–609. http://dx.doi.org/10.1137/070704277.

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45

Morita, Hiroshi, and Hiroaki Ishii. "A stochastic improvement method for stochastic programming." Computational Statistics & Data Analysis 14, no. 4 (1992): 477–87. http://dx.doi.org/10.1016/0167-9473(92)90063-l.

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46

Rhodes, Remi. "Stochastic Homogenization of Reflected Stochastic Differential Equations." Electronic Journal of Probability 15 (2010): 989–1023. http://dx.doi.org/10.1214/ejp.v15-776.

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47

Higle, J. L., B. Rayco, and S. Sen. "Stochastic scenario decomposition for multistage stochastic programs." IMA Journal of Management Mathematics 21, no. 1 (2009): 39–66. http://dx.doi.org/10.1093/imaman/dpp001.

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48

Du, Shouqiang, Maolin Che, and Yimin Wei. "Stochastic structured tensors to stochastic complementarity problems." Computational Optimization and Applications 75, no. 3 (2019): 649–68. http://dx.doi.org/10.1007/s10589-019-00144-3.

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49

Sun, Ran, and Yueyue Fan. "Stochastic OD demand estimation using stochastic programming." Transportation Research Part B: Methodological 183 (May 2024): 102943. http://dx.doi.org/10.1016/j.trb.2024.102943.

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50

Hu, Peng, та Chengming Huang. "Stability of stochasticθ-methods for stochastic delay integro-differential equations". International Journal of Computer Mathematics 88, № 7 (2011): 1417–29. http://dx.doi.org/10.1080/00207160.2010.509430.

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