Fuzzy Logic and Linguistic Variables

The concept of the fuzzy set was introduced over 30 years ago by Zadeh. After being neglected for many years, it was rediscovered in the mid-1980s for regulation in microelectronics, automatic process control, and operations research. At present, fuzzy set theory has many applications in a large variety of different fields. The reader is referred to the literature for detailed examples. 

One of the most important tools in applications of fuzzy set theory is the concept of linguistic variables (LV). These are groups of fuzzy sets with (partially) overlapping membership functions over a common (crisp) basic variable x. To represent several classes within an LV, the membership functions should cover all the relevant definition space of the basic variable x. The overlaps of these functions define the fuzziness. A linguistic variable L, classified by n fuzzy sets Aj, can be defined as 

Segmentation of Molecular Surfaces with Linguistic Variables 

The segmentation of molecular surfaces can be carried out on the basis of different surface qualities.Here we shall focus on a segmentation with respect to topographical criteria. The shape analysis is based on the surface topography index (STI) described previously. Following Heiden and Brickmann, a six class linguistic variable 

Similarity/dissimilarity obviously plays an important role in all pattern recognition problems. The vagueness of this term itself suggests that there are numerous ways in which the dissimilarity D of two objects a and b may be defined, depending on the actual problem. Segmentation of molecular 

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