Об одном подходе к имитационному моделированию спортивной игры с непрерывным временем
This paper is dedicated to discussing methods of statistical modeling the outcomes of sport events and, particularly, matches with continuous time. We propose a simulation-based approach to predicting the outcome of a match, somehow medium between pure statistical methods and agent simulation of individual players. An example of retrospective prediction is given.
This article concerns the problem of predicting the size of company's customer base in case of solving the task of managing its clients. The author purposes a new approach to segment-oriented predicting the size of clients based on adopting the Staroverov's employees moving model. Besides the article includes the limitations of using this model and its modification for each type of relations of the client and the company.
The monograph presents results by professor Dr. A. Shalumov’s Research School of Modeling, Information Technology and Automated Systems (Russia). The program, ASONIKA, developed by the school is reviewed here regarding reliability and quality of devices for simulation of electronics and chips during harmonic and random vibration, single and multiple impacts, linear acceleration and acoustic noise, and steady-state and transient thermal effects. Calculations are done for thermal stress during changes in temperature and power in time. Calculations are done for number of cycles to fatigue failure under mechanical loads as well as under cyclic thermal effects. Simulation results for reliability analysis are taken into account. Models, software interface, and simulation examples are presented.
For engineers and scientists involved in design automation of electronics.
Nested Petri nets (NP-nets) are Petri nets with net tokens - an extension of high-level Petri nets for modeling active objects, mobility and dynamics in distributed systems. In this paper we present an algorithm for translating two-level NP-nets into behaviorally equivalent Colored Petri nets with the view of applying CPN methods and tools for nested Petri nets analysis. We prove, that the proposed translation preserves dynamic semantics in terms of bisimulation equivalence.
Financial markets have always been attractive as a means of increasing one's wealth, and those who make accurate predictions take the prize. Forecasting models such as linear ones are simple to compute, however, they give rough approximations of the underlying relationships in the data, thus, producing poor forecasts. The solution to this issue could be the nonlinear models which try to fit the data and display the relationships with higher accuracy. Previous research seems to prove this statement from the statistician's point of view which might be of little use for an investor. Therefore, the focus of this paper is on the comparison of three types of models (nonlinear: ANN, STAR, and linear: AR) in terms of financial performance. Our research is based on the initial code for GAUSS and papers by Dick van Dijk. The data used is the monthly S&P 500 Index values from 1970 to 2012 provided by the Robert Shiller's website. Forecasting index changes begins at 1995 and ends in 2012 providing up-to-date results for 14 model specifications. The best model proves to be the flexible ANN, beating the linear AR in the majority of cases, leaving the underperforming heavy-parameterized STAR model behind. Thus, it is evident that the more flexible nonlinear models outperform the heavily parameterized ones as well as linear models for the S&P 500 Index. The introduced type of performance evaluation has a more comprehensible application to the financial market analysis.
In the paper integrated information systems for corporate planning and budgeting are considered. Four groups of practical tasks exceeding the bounds of typical functionality of special-purpose planning and budgeting information systems are allocated. Several classes of information systems (simulation, statistical analysis, financial analysis and modeling, group decision making, business intelligence), which may provide the completeness of corporate planning and budgeting are denoted as solutions complementary to special-purpose planning and budgeting systems.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.