Abstract
In previous chapters the linguistic information has always been modelled by means of linguistic terms uniformly and symmetrically distributed in a linguistic term set, because it performs and adapts well to many problems. However, on some occasions the necessity of dealing with symmetrically distributed nonuniform terms in the scales arises because the problem needs preference scales in which one side of the scale has a greater granularity than the other. The managing of such a type of linguistic unbalanced scales is quite challenging for Computing with Words even more if precise, linguistic, and easily understandable results are required. This chapter describes a methodology to deal with unbalanced linguistic information that not only facilitates computation with this type of information, but also provides a fuzzy representation that guarantees precise and linguistic results by using the 2-tuple linguistic model.
Published Version
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