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Taking Account of Uncertain, Imprecise and Incomplete Data in Sustainability Assessments in Agriculture

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Computational Science and Its Applications – ICCSA 2014 (ICCSA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8581))

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Abstract

To manipulate incomplete, uncertain and hypothetic information about farms, the future evaluation software in the agriculture domain will have to make computations and combine fuzzy numerical values. The approach we propose relies on combination of incomplete, uncertain and hypothetic object values based on particular application of the Dempster-Shafer evidence theory. We then propose the integration of this approach in classic object oriented programming via the implementation of a C++ library.

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Author information

Authors and Affiliations

  1. Agri’terr, Esitpa, Mont-Saint-Aignan, France

    Jérôme Dantan & Salima Taibi

  2. CNAM, CEDRIC, Paris, France

    Jérôme Dantan & Yann Pollet

Authors
  1. Jérôme Dantan
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  2. Yann Pollet
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  3. Salima Taibi
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Editor information

Editors and Affiliations

  1. School of Engineering, University of Basilicata, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Sanjay Misra

  3. Department of Production and Systems, University of Minho, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  4. DICAR, Polytecnico di Bari, 70125, Bari, Italy

    Carmelo Torre

  5. University of Minho, Braga, Portugal

    Jorge Gustavo Rocha  & Maria Irene Falcão  & 

  6. Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics,, Kyushu Sangyo University, 2-3-1 Matsukadai, 813-8503, Higashi-ku, Fukuoka, Japan

    Bernady O. Apduhan

  8. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

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© 2014 Springer International Publishing Switzerland

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Dantan, J., Pollet, Y., Taibi, S. (2014). Taking Account of Uncertain, Imprecise and Incomplete Data in Sustainability Assessments in Agriculture. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8581. Springer, Cham. https://doi.org/10.1007/978-3-319-09150-1_46

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  • DOI: https://doi.org/10.1007/978-3-319-09150-1_46

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09149-5

  • Online ISBN: 978-3-319-09150-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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