Dynamic processes forecasting and risk estimation under uncertainty using decision support systems

The paper considers the problem of decision support systems constructing for solving the problems of modeling and estimating selected types of risks with the possibility for application of alternative data processing techniques, modeling and estimation of parameters and states for the processes under study. The system proposed has a modular architecture that provides a possibility for easy extension of its functional possibilities with new parameter estimation techniques, forecasting methods, risk estimation procedures, and alternatives generation. High quality of the final result is achieved thanks to appropriate tracking of the computational processes at all data processing stages: preliminary data processing, model structure and parameter estimation, computing of short- and middle-term forecasts, and estimation of risk variables (parameters) as well as thanks to convenient for a user intermediate and final results representation. The system is based on the ideologically different techniques of modeling and risk forecasting what creates a convenient basis for combining of various approaches to achieve the best results. Examples of the system application show that it could be used successfully for solving practical problems of different kinds of risk estimation.