Similarity measure for aggregated fuzzy numbers from interval-valued
  data
  This paper presents a method to compute the degree of similarity between two
aggregated fuzzy numbers from intervals using the Interval Agreement Approach
(IAA). The similarity measure proposed within this study contains several
features and attributes, of which are novel to aggregated fuzzy numbers. The
attributes completely redefined or modified within this study include area,
perimeter, centroids, quartiles and the agreement ratio. The recommended
weighting for each feature has been learned using Principal Component Analysis
(PCA). Furthermore, an illustrative example is provided to detail the
application and potential future use of the similarity measure.
