The clustering problem is cast in the framework of possibility theory. The approach differs from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values can be interpreted as degrees of possibility of the points belonging to the classes, i.e., the compatibilities of the points with the class prototypes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data is constructed, and the membership and prototype update equations are derived from necessary conditions for minimization of the criterion function. The advantages of the resulting family of possibilistic algorithms are illustrated by several examples. >

http://systemaut.persiangig.com/Fuzzy/IEEE_00227387.pdf

A possibilistic approach to clustering

Theory of fuzzy integrals and its applications

A rating scale for drug-induced akathisia has been derived that incorporates diagnostic criteria for pseudoakathisia, and mild, moderate, and severe akathisia. It comprises items for rating the observable, restless movements which characterise the condition, the subjective awareness of restlessness, and any distress associated with the akathisia. In addition, there is an item for rating global severity. A standard examination procedure is recommended. The inter-rater reliability for the scale items (Cohen's kappa) ranged from 0.738 to 0.955. Akathisia was found in eight of 42 schizophrenic in-patients, and nine had pseudoakathisia, where the typical sense of inner restlessness was not reported.

A rating scale for drug-induced akathisia

Aggregation of information is of primary importance in the construction of knowledge based systems in various domains, ranging from medicine, economics, and engineering to decision-making processes, artificial intelligence, robotics, and machine learning. This book gives a broad introduction into the topic of aggregation functions, and provides a concise account of the properties and the main classes of such functions, including classical means, medians, ordered weighted averaging functions, Choquet and Sugeno integrals, triangular norms, conorms and copulas, uninorms, nullnorms, and symmetric sums. It also presents some state-of-the-art techniques, many graphical illustrations and new interpolatory aggregation functions. A particular attention is paid to identification and construction of aggregation functions from application specific requirements and empirical data. This book provides scientists, IT specialists and system architects with a self-contained easy-to-use guide, as well as examples of computer code and a software package. It will facilitate construction of decision support, expert, recommender, control and many other intelligent systems.

József Dombi

Papers

A general class of fuzzy operators, the demorgan class of fuzzy operators and fuzziness measures induced by fuzzy operators

Membership function as an evaluation

Basic concepts for a theory of evaluation: The aggregative operator

A method for determining the weights of criteria: the centralized weights

The approximation of piecewise linear membership functions and Łukasiewicz operators