Snytyuk V. Evolutionary technologies of decision making under uncertainties

Dissertation is devoted to decision of the important research problem of efficiency increasing of the decision making processes by creation of the complex technical systems in way of models, methods and applications development of identifications and forecasting in uncertainty conditions on the base of evolutionary paradigms. The concept of information-analytical accompaniment of the complex technical system on stage its life cycle, which is concluded in use the elements composition of four scientific paradigms: life cycle programming, system approach and system analysis, evolutionary modelling and information preprocessing, is offered. Such integration is directed on the uncertainties reduction on initial stage of the life cycle systems to account objectivity of expert conclusion and hipping being absent information by prediction and technological forecasting. In their base lies need of the identifications and optimization problems decision on the base of evolutionary paradigms that expects use of evolutionary algorithms as for structured and parametric identification objective function, so and for searching their best values. Methods of identification and optimization for complex dependencies on the base of composite using Soft Computing technologies are developed. Methods of the information increasing for source data, as well as evolutionary methods to clustering and renewal data gaps are offered. Technology of the expert's qualification determination on base of the unbiasedness axiom is improved and technology for subjective conclusions objectivity is offered. Practical applications of offered evolutionary models and methods are considered and on their validity and efficiencies is specified.