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- W3110958920 abstract "Method preliminary fractional analysis is designed in this article for building of prediction neural networks (PNN) for the following forecast of the behaviour of the converter inverting type (ISN-3). The Method is founded on fractal analysis output univariate signal enterring from generating systems (in this instance from ISN-3) presented in the manner of black box. The Sequence of the analysis following: determination by means of author's method temporary lag's row and his(its) phase shift, shaping the temporary row, reconstruction by means of method delay attractors in pseudo-phase space and calculation by means of Grassberger's-Procachchia's method his(its) maximum dimensionality of the embedding and correlation dimensional. It Is Entered notion to reconstructions attractors in pseudo-phase space on Taken's method. Is it Hereinafter built PNN: is chose her(its) structure, is described principle to realization of the time delay for PNN. Learning the got networks was conducted on Levenberg's-Markvardt's gradient method. The Best forecast of the behaviour ISN-3 was received by means of network, built on the base Multilayer Perceptron (MP) with one hidden layer and configuration MP 14:14:1. For this neural network comparison result of the forecasting with independent test beside gave the coincidence beside 8-13 periods (depending on chosen area of the test row)." @default.
- W3110958920 created "2020-12-21" @default.
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- W3110958920 date "2010-06-15" @default.
- W3110958920 modified "2023-09-25" @default.
- W3110958920 title "Fractal analysis of discrete-nonlinear systems and building prediction neural networks on its base, on example of the converter, working in chaotic mode" @default.
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