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Object of research - dynamic lines of quotations of currencies and securities in the world financial and share markets. Method of research - the analytical imitating analysis. The purpose of work - neural networks method of forecasting with use of genetic algorithms for formation of forecasts in dilling information systems. The neural networks methodology finds all new successful applications in practice of management and decision-making, including - in financial and trading spheres. The theory of nonlinear adaptive systems laying in its basis has proved the utility at development of forecasts in a lot of branches of economy and the finance. The rate of functioning of the enterprise depends on the long-term forecasts, the current management demands presence of short-term forecasts. The purpose of the given work is studying experience of experts in the field of forecasting the financial markets with use artificial neural networks with application of genetic algorithms for forecasting in dilling information systems and uses of the forecast in bank dilling information systems. Models of neural networks for bank dilling information - the systems are offered to attestative work, allowing to spend the analysis of the financial and share markets, to provide support of decision-making. Approaches, to a choice of structure of model are analyzed. Self-learning mathematical models of neural networks, and also procedures of the analysis of the initial data are developed.