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Rule Learning in a Fuzzy Decision Support System for the Environmental Risk Assessment of GMOs

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Abstract

Aim of the paper is the application of a Learning Classifier System (LCS) to learn the inference rules in a Fuzzy Decision Support System (FDSS). The FDSS is used for the Environmental Risk Assessment (ERA) of the deliberate release of genetically modified plants. The evaluation process permits identifying potential impacts that can achieve one or more receptors through a set of migration paths. The risk assessment in the FDSS is obtained by using a Fuzzy Inference System performed using jFuzzyLogic library. For the human experts might be hard developing complex FISs. We propose to use a LCS for automatically learning the appropriate fuzzy rules from the questionnaires produced by notifiers, named Fuzzy Rule Learning System (FRLS). FRLS is based on a special kind of LCS, namely the eXtended Classifier System (XCS). The derived rules have been validated on real world cases by the human experts that are in charge of ERA.

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Author information

Authors and Affiliations

  1. Dept. of Science and Technology, University of Naples “Parthenope”, Isola C4, Centro Direzionale, I-80143, Napoli, NA, Italy

    Francesco Camastra, Angelo Ciaramella, Salvatore Sposato, Antonino Staiano & Alfredo Starace

  2. Nature Protection Dept., Institute for Environmental Protection and Research (ISPRA), via v. Brancati 48, 00144, Roma, Italy

    Valeria Giovannelli, Matteo Lener, Valentina Rastelli & Giovanni Staiano

Authors
  1. Francesco Camastra

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  2. Angelo Ciaramella

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  3. Valeria Giovannelli

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  4. Matteo Lener

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  5. Valentina Rastelli

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  6. Salvatore Sposato

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  7. Antonino Staiano

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  8. Giovanni Staiano

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  9. Alfredo Starace

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Editor information

Editors and Affiliations

  1. DIBRIS, University of Genoa, Via Dodecaneso 35, 16146, Genoa, Italy

    Francesco Masulli

  2. Dept. of Informatics, Systems, and Communication, University of Milano Bicocca, Viale Sarca 336, 20126, Milan, Italy

    Gabriella Pasi

  3. Dept. of Information Systems, Iona College, 710 North Ave, 10801, New Rochelle, NY, USA

    Ronald Yager

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© 2013 Springer International Publishing Switzerland

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Camastra, F.et al. (2013). Rule Learning in a Fuzzy Decision Support System for the Environmental Risk Assessment of GMOs. In: Masulli, F., Pasi, G., Yager, R. (eds) Fuzzy Logic and Applications. WILF 2013. Lecture Notes in Computer Science(), vol 8256. Springer, Cham. https://doi.org/10.1007/978-3-319-03200-9_23

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