Abstract
The article proposes a methodology for modeling and forecasting economic, financial and environmental processes, based on the principles of system analysis and combined models, including linear and non-linear regression models, as well as probabilistic models in the form of Bayesian networks. The basis of the methodology is tracking the computational processes of processing statistical data at all stages using the appropriate sets of statistical quality criteria. The high quality of the intermediate and final results is achieved through the application of statistical quality criteria to the data, the adequacy of the model and the quality of forecasts. The methodology is used in a specialized decision support system aimed at analyzing nonlinear non-stationary processes in various fields.
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Bidyuk, P., Gozhyj, A., Matsuki, Y., Kuznetsova, N., Kalinina, I. (2021). Modeling and Forecasting Economic and Financial Processes Using Combined Adaptive Models. In: Babichev, S., Lytvynenko, V., Wójcik, W., Vyshemyrskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-54215-3_25
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DOI: https://doi.org/10.1007/978-3-030-54215-3_25
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