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Predicting Trends in Cereal Production in the Czech Republic by Means of Neural Networks

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  • Malinovský, Vít

Abstract

This paper deals with problems of processing agricultural production data into the form of time series and analysing consequent results by means of two completely different methods. The first method for calculating cereals production figures uses the MS-Excel spreadsheet using conventional mathematical and statistical functions while the second one uses the ELKI software providing users with development environment including algorithms of neural networks. The obtained results are similar to a certain extent which shows new possibilities of progressive use of neural networks in future and enables modern approach to analysing time series not only in agricultural sector.

Suggested Citation

  • Malinovský, Vít, 2021. "Predicting Trends in Cereal Production in the Czech Republic by Means of Neural Networks," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 13(1), March.
    • Handle: RePEc:ags:aolpei:320250
    DOI: 10.22004/ag.econ.320250
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    References listed on IDEAS

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    1. Edward B. Barbier & Johnson Gwatipedza & Duncan Knowler & Sarah H. Reichard, 2011. "The North American horticultural industry and the risk of plant invasion," Agricultural Economics, International Association of Agricultural Economists, vol. 42, pages 113-130, November.
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