In this chapter, a soft fusion approach of a set of aligned registered images is described, in which each image represents a distinct theme of the same territory. The objective of the fusion is to evaluate the spatial units of the territory, pixels or cells, by a group of experts through associating to the spatial units scores representing their suitability as best locations with respect to given criteria expressed by soft constraints. The decision process first determines automatically the coherence among a majority of experts' evaluations with respect to each given criterion and then computes the coherent evaluation of the criterion representing the majority opinion. Finally, it computes the overall coherent evaluation with respect to a majority of the criteria that is used to rank the spatial units. The fuzzy majority is defined by linguistic quantifiers; the coherence among a fuzzy majority of experts is defined based on the Minkowski OWA operators while the fuzzy majority of coherent evaluations is modeled by an Induced OWA operator.
A Multi Criteria Group Decision Making Process Based on the Soft Fusion of Coherent Evaluations of Spatial alternatives
Gloria Bordogna;Simone Sterlacchini
2014
Abstract
In this chapter, a soft fusion approach of a set of aligned registered images is described, in which each image represents a distinct theme of the same territory. The objective of the fusion is to evaluate the spatial units of the territory, pixels or cells, by a group of experts through associating to the spatial units scores representing their suitability as best locations with respect to given criteria expressed by soft constraints. The decision process first determines automatically the coherence among a majority of experts' evaluations with respect to each given criterion and then computes the coherent evaluation of the criterion representing the majority opinion. Finally, it computes the overall coherent evaluation with respect to a majority of the criteria that is used to rank the spatial units. The fuzzy majority is defined by linguistic quantifiers; the coherence among a fuzzy majority of experts is defined based on the Minkowski OWA operators while the fuzzy majority of coherent evaluations is modeled by an Induced OWA operator.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.