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Fuzzy Measures and Experts’ Opinion Elicitation

An Application to the FEEM Sustainable Composite Indicator

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Advances in Neural Networks: Computational and Theoretical Issues

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 37))

Abstract

To over pass the limits inherent in liner models, suitable aggregation operators are required, taking into account interactions among the criteria. This becomes more and more crucial in Decision Theory, where all the information can be inferred by one or more Experts, using an ad hoc questionnaire. This is the case of the FEEM SI sustainability index, a composite geo-referenced index which aggregates several economic, social and environmental dimensions-structured in a decision tree- into a single number between zero (the worst sustainable country) and one (the best one). Fuzzy measure (non additive measures) are here proposed for the aggregation phase. To this purpose, each intermediate node of the structure combines the values of the sub-nodes using a model based on second-order non additive measure. To infer the value of the measure for each node, a suitable questionnaire has been fulfilled by a set of Experts, and the obtained answers were processed using an optimization algorithm. To guarantee the strict convexity of the algorithm, the questionnaire needs to be carefully designed. The individual measures are subsequently aggregated and the numerical results permitted to compare the sustainability of all the considered territorial units.

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Author information

Authors and Affiliations

  1. Mediterranean Center for Climate Change (CMCC), Bologna, Italy

    Luca Farnia

  2. Fondazione Eni Enrico Mattei, Venice, Italy

    Luca Farnia & Silvio Giove

  3. University Cà Foscari, Venice, Italy

    Silvio Giove

Authors
  1. Luca Farnia
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  2. Silvio Giove
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Correspondence to Luca Farnia .

Editor information

Editors and Affiliations

  1. Computer Science Department, University of Milano, Milano, Italy

    Simone Bassis

  2. Dipartimento di Psicologia & Vietri sul Mare (SA), Seconda Universitá di Napoli, International Institute for Advanced Scientific Studies (IIASS), Caserta, Italy

    Anna Esposito

  3. Department of Civil, Environmental, Energy, and Material Engineering, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

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Farnia, L., Giove, S. (2015). Fuzzy Measures and Experts’ Opinion Elicitation. In: Bassis, S., Esposito, A., Morabito, F. (eds) Advances in Neural Networks: Computational and Theoretical Issues. Smart Innovation, Systems and Technologies, vol 37. Springer, Cham. https://doi.org/10.1007/978-3-319-18164-6_22

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  • DOI: https://doi.org/10.1007/978-3-319-18164-6_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18163-9

  • Online ISBN: 978-3-319-18164-6

  • eBook Packages: EngineeringEngineering (R0)

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