2003Journal of Changchun University of TechnologyRequires access

The Application of BP Neural Network in the Prediction of Non-Linear Time Sequence

Lin Xiao He

Open publisher page 1 citations

Abstract

Neural Networks are briefly disussed,and a model of time sequence object is set up according to Kolmogorov continuity theorem. The method of data processing on the basis of this model is then explored. The correctness of this model is confirmed through forecasting the quantities of national stock.

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What this paper is about

Neural Networks are briefly disussed,and a model of time sequence object is set up according to Kolmogorov continuity theorem. The method of data processing on the basis of this model is then explored. The correctness of this model is confirmed through forecasting the quantities of national stock.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Neural Networks are briefly disussed,and a model of time sequence object is set up according to Kolmogorov continuity theorem. The method of data processing on the basis of this model is then explored. The correctness of this model is confirmed through forecasting the quantities of national stock.

Key concepts: Correctness, Artificial neural network, Sequence (biology), Time sequence, Computer science, Set (abstract data type), Algorithm, Basis (linear algebra)

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