Inductive Learning Algorithms for Complex Systems Modeling
Inductive Learning Algorithms for Complex Systems Modeling
Systems Analysis Modelling Simulation - Special issue: Self-organising modelling and simulation
Self-organising modelling as a part of simulation process
Systems Analysis Modelling Simulation - Special issue: Self-organising modelling and simulation
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Theories and algorithms developed for pattern recognition can be applied to random processes forecasting and for solution of all another interpolation type problems of artificial intelligence. For this purpose input data sample in the form of time series should be transformed into simultaneous form according to rules of Gauss conditional equations complication. Examples of algorithms used in pattern recognition are considered. Particularly is considered algorithm of secondary arguments generation. It is proposed to use error of modelling as effective secondary argument in special twice-multilayered neural network. Another GMDH network is considered as inductive analogue of Kalman type noise filter and as network, which interpolates non-linear objects characteristics.