This contribution is deemed in the view of the authors, as a methodological proposal in order to employ the well known fuzzy approach in a context of operational risk management. Even though the available data can not be considered native fuzzy, we show that modelling them according to fuzzy intervals is useful from two point of view: it allows to take into account and to exploit more informati...

A new more informative and effective fuzzy discriminant analysis method based on fuzzy regression with point prototypes has been developed and applied on two relevant data sets (the classical Fisher’s Iris data set and a clinical data set concerning different diseases). The proposed fuzzy method is consistent with the supervised character of the original discriminant analysis method. The classi...

*L.T. Tran, M.A. Ridgley, and R. Sutherland, University of Hawaii, Geography Department, 2424 Maile Way, Honolulu, HI 96822, USA; M.A. Nearing, National Soil Erosion Laboratory, USDA-ARS, West Lafayette, IN 47907-1196, USA; L. Duckstein, Ecole Nationale du Genie Rural, des Eaux et des Forets, 19 avenue du Maine, 75732 Paris Cedex 15, France. *Corresponding author: [email protected]. Current address:...

The main problem when dealing with fuzzy data variables is that it cannot be formed by a model represents the through method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates invalidity in case existence multicollinearity. To overcome this problem, Bridge Regression (FBRE) Method was relied upon to estimate linear regression triangular numbers. Moreover, detection multicolline...

We evaluated three mathematical procedures to estimate the parameters of the relationship between weight and length for Cichla monoculus: least squares ordinary regression on log-transformed data, non-linear estimation using raw data and a mix of multivariate analysis and fuzzy logic. Our goal was to find an alternative approach that considers the uncertainties inherent to this biological model...

Relationships between geographically referenced variables are usually spatially heterogeneous and, to account for such variations, local models are necessary. This paper compares the Geographically Weighted Regression (GWR) model, usually used to integrate and examine the spatial heterogeneity of a relationship, and the Fuzzy Clustering-Based Least Squares (FCBLS) model for the analysis of spat...