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Assessment of Fertilizer Nitrogen Requirement of Sugar Beetroot Using Info-Gap Theory

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Artificial Intelligence and Soft Computing (ICAISC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9120))

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Abstract

The aim of this paper is to present an interesting application of one of the decision-making methods used in problems with lack of knowledge. This method is called Info-Gap Theory and can be applied to describe the phenomenon where no classic uncertainty description in form of probability density or possibility distribution is at disposal. A general outline of Info-Gap Theory is presented and its functions (robustness and opportuneness) are shown. The numerical example of fertilizer nitrogen requirement is given to illustrate the efficiency of the proposed method to practical issues.

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Author information

Authors and Affiliations

  1. West Pomeranian University of Technology, Zolnierska 49, 71-210, Szczecin, Poland

    Andrzej Piegat & Karina Tomaszewska

Authors
  1. Andrzej Piegat
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  2. Karina Tomaszewska
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Corresponding author

Correspondence to Andrzej Piegat .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Czestochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Czestochova Univ of Technology, Częstochova, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2015 Springer International Publishing Switzerland

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Piegat, A., Tomaszewska, K. (2015). Assessment of Fertilizer Nitrogen Requirement of Sugar Beetroot Using Info-Gap Theory. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_40

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  • DOI: https://doi.org/10.1007/978-3-319-19369-4_40

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19368-7

  • Online ISBN: 978-3-319-19369-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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