Vyacheslav Zelentsov

Multiple models of information fusion processes: Quality definition and estimation

Abstract Now problems of a multi-criteria quality estimation of models as well as a justified selection of task-oriented models are still not investigated thoroughly enough. The importance of the problems increases when a research object is described not via a single model, but with a set or a complex of multiple models including models from different classes or combined models such as combined analytical-simulation models, logical-algebraic ones, etc. The aforementioned problems are being investigated within the theory of model quality control. The description of main elements of this theory and its applications is the primary goal of the paper.

Development of intelligent information systems for operational river-flood forecasting

The structural framework and practical implementation of operational river flood forecasting systems, based on integrated use of state-of-the-art information technologies and hydrological simulation methods, are described. They exemplify the practical implementation of an interdisciplinary approach that uses broadly the Earth’s remote sensing data, service architecture–based forecasting systems, and an intelligent interface to select the type and adjust the parameters of hydrological models, providing the interpretation, user-friendly representation, and accessibility of forecast results as web services. A practical trial of the system’s prototype proved the possibility to obtain high-accuracy operational (from several hours to several days) forecasts for the inundation areas and depths of river valley sections.

Complex Objects Remote Sensing Forest Monitoring and Modeling

In this paper the concept of integrated modeling and simulation processes of the Complex Natural and Technological Object (CNTO) is presented. The main goal of the investigations consists in the practice of the predetermined modeling. The practice direction as the remote sensing forest monitoring is proposed by the authors. Here the methodical foundations of the integrated modeling and simulation, the process of CNTO operation, the technology of the remote sensing forest monitoring are considered. Principal concern is attended to the continuity of the model and object solving practical issues. More over results of CNTO remote sensing forest monitoring make it possible to adapt models of this system to changing environment conformably to the forest management.

Intelligent Integrated Decision Support Systems for Territory Management

This study proposes a scientific and methodical approach to problem solving automation, and intellectualization of multi-criteria decision-making processes for territory management. The substantiation of the composition and structure of the Integrated Intelligent Decision Support System (IIDSS) in management areas is based on a methodology developed by the authors and technologies of proactive monitoring and management of the structural dynamics of complex objects.

Models Adaptation of Complex Objects Structure Dynamics Control

In this paper we present a dynamic multiple criteria model of integrated adaptive planning and scheduling for complex objects (CO). Various types of CO are in use currently, for example: virtual enterprises, supply chains, telecommunication systems, etc. Hereafter, we refer to CO as systems of those types. The adaptation control loops are explicitly integrated within the model of analytical simulation. The mathematical approach is based on a combined application of control theory, operations research, systems analysis, and modeling and simulation theory. In particular, a scheduling problem for CO is considered as a dynamic interpretation. New procedures of dynamic decomposition help us to find the parameter values of the model’s adaptation. The example demonstrates a general optimization scheme to be applied to the problem of division of competencies between the coordinating and operating levels of the CO via parametric adaptation of the model’s described structure dynamics control processes.