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  • Artificial neural networks provide powerful tools for linear and nonlinear system modeling and prediction. They are commonly used in various fields, such as economics, medicine, industry, aerospace, chemistry etc. Artificial neural networks are capable comprehend single input – single output as well as multiple input – multiple output functions. This paper is focused on prediction of non-artificial time series that are typically considered as single input – single output systems from the point of view of the predictor. The paper presents study of the influence of the input vector length to prediction quality. All simulations were done in MATLAB.
  • Artificial neural networks provide powerful tools for linear and nonlinear system modeling and prediction. They are commonly used in various fields, such as economics, medicine, industry, aerospace, chemistry etc. Artificial neural networks are capable comprehend single input – single output as well as multiple input – multiple output functions. This paper is focused on prediction of non-artificial time series that are typically considered as single input – single output systems from the point of view of the predictor. The paper presents study of the influence of the input vector length to prediction quality. All simulations were done in MATLAB. (en)
Title
  • Time Series Prediction Using Artificial Neural Networks: Influence of The Input Vector Size
  • Time Series Prediction Using Artificial Neural Networks: Influence of The Input Vector Size (en)
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  • Time Series Prediction Using Artificial Neural Networks: Influence of The Input Vector Size
  • Time Series Prediction Using Artificial Neural Networks: Influence of The Input Vector Size (en)
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  • RIV/70883521:28110/12:43869249!RIV13-MSM-28110___
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  • P(ED2.1.00/03.0089)
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  • 174464
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  • RIV/70883521:28110/12:43869249
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  • artificial neural network, time series, prediction, benchmark,Santa Fe competition, Matlab (en)
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  • Recent Researches in Circuits and Systems
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  • Sámek, David
  • Vařacha, Pavel
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issn
  • 1790-5117
number of pages
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  • WSEAS Press (GR)
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  • 978-1-61804-108-1
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  • 28110
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