BMAP/G/1/∞ system with last come first served probabilistic priority

Consideration was given to the BMAP/G/1/∞ single-server queuing system with batch Markov arrivals, arbitrary servicing, finite-capacity buffer, and last come first served probabilistic priority. Equations for determination of the stationary probabilities of states and stationary characteristics associated with the time of customer sojourn in the system were determined.     

A class of systems of bilinear integral Volterra equations of the first kind of the second order

A class of bilinear systems of integral Volterra equations of the first kind related to the problem of automatic control of a nonlinear dynamic system (object) with unknown structure and vector input and output is studied. Algorithms for an analytic solution to corresponding bilinear systems and its numerical approximation are developed. A special character of the algorithms is illustrated by model examples.     

Consistency constraints and 3D building reconstruction

Virtual architectural (indoor) scenes are often modeled in 3D for various types of simulation systems. For instance, some authors propose methods dedicated to lighting, heat transfer, acoustic or radio-wave propagation simulations. These methods rely in most cases on a volumetric representation of the environment, with adjacency and incidence relationships. Unfortunately, many buildings data are only given by 2D plans and the 3D needs varies from one application to another. To face these problems, we propose a formal representation of consistency constraints dedicated to building interiors and associated with a topological model. We show that such a representation can be used for: (i) reconstructing 3D models from 2D architectural plans (ii) detecting automatically geometrical, topological and semantical inconsistencies (iii) designing automatic and semi-automatic operations to correct and enrich a 2D plan. All our constraints are homogeneously defined in 2D and 3D, implemented with generalized maps and used in modeling operations. We explain how this model can be successfully used for lighting and radio-wave propagation simulations.     

On the properties of the identically singular Lagrange problem

We consider the identically singular Lagrange problem of the calculus of variations. It is investigated how the conjugate points and the Jacobi equation index are related to the solvability conditions of the appropriate matrix Riccati equation and the reducibility of the functional to a perfect square. The criterion of the trajectory variation smallness at a small variation of the functional in the neighborhood of the extremal is obtained.     

Control of complex ecological-economic systems

The paper is devoted to developing methods for control of ecological-economic systems consisting of three hierarchically subordinate subjects of control. In describing the dynamics of a system state, equations in partial derivatives that are solved numerically according to a semi-implicit scheme of the finite-difference method are used. To achieve its main goal (maintenance of an ecological subsystem in stable state), the subject of control of the upper level applies different control methods. Methods of hierarchical control (motivation, enforcement, and persuasion) that differ in the direction of action (on the objective function or domain of admissible controls) are proposed; examples of their use are represented and a comparative analysis of the obtained results is made.     

Minimum of power consumption in the problem of oscillation damping

Consideration was given to minimization of the L ¹-norm of control of the linear oscillatory system. For consumption of the energy resources required to damp oscillations, bilateral estimates were obtained.     

Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems

This paper presents a new approach to Particle Swarm Optimization, called Michigan Approach PSO (MPSO), and its application to continuous classification problems as a Nearest Prototype (NP) classifier. In Nearest Prototype classifiers, a collection of prototypes has to be found that accurately represents the input patterns. The classifier then assigns classes based on the nearest prototype in this collection. The MPSO algorithm is used to process training data to find those prototypes. In the MPSO algorithm each particle in a swarm represents a single prototype in the solution and it uses modified movement rules with particle competition and cooperation that ensure particle diversity. The proposed method is tested both with artificial problems and with real benchmark problems and compared with several algorithms of the same family. Results show that the particles are able to recognize clusters, find decision boundaries and reach stable situations that also retain adaptation potential. The MPSO algorithm is able to improve the accuracy of 1-NN classifiers, obtains results comparable to the best among other classifiers, and improves the accuracy reported in literature for one of the problems.

Amoeba-based Chaotic Neurocomputing: Combinatorial Optimization by Coupled Biological Oscillators

We demonstrate a neurocomputing system incorporating an amoeboid unicellular organism, the true slime mold Physarum, known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing optical feedback applied according to a recurrent neural network model, we induce that the amoeba’s photosensitive branches grow or degenerate in a network-patterned chamber in search of an optimal solution to the traveling salesman problem (TSP), where the solution corresponds to the amoeba’s stably relaxed configuration (shape), in which its body area is maximized while the risk of being illuminated is minimized.Our system is capable of reaching the optimal solution of the four-city TSP with a high probability. Moreover, our system can find more than one solution, because the amoeba can coordinate its branches’ oscillatory movements to perform transitional behavior among multiple stable configurations by spontaneously switching between the stabilizing and destabilizing modes. We show that the optimization capability is attributable to the amoeba’s fluctuating oscillatory movements. Applying several surrogate data analyses, we present results suggesting that the amoeba can be characterized as a set of coupled chaotic oscillators.

Betriebsinformatik und Wirtschaftsinformatik als notwendige anwendungsbezogene Ergänzung einer allgemeinen Informatik – Vorschläge zur Verbesserung der akademischen Ausbildung auf dem Gebiet der automatisierten Datenverarbeitung in der Bundesrepublik Deutschland

Zusammenfassung  Nachdruck eines Aufsatzes aus elektronische datenverarbeitung 11(11)1969:544–548. This article is also available in English via and : Grochla E (2008) Corporate Information Systems Engineering and Business and Information Systems Engineering as a Necessary Application-Oriented Extension of General Computer Science – Proposals for Enhancing Academic Education in the Field of Automated Data Processing in the Federal Republic of Germany. Bus Inf Syst Eng. doi .

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