It has been recognised that formal methods are useful as a modelling tool in requirements engineering. Speci cation languages such as Z permit the precise and unambiguous modelling of system properties and behaviour. However some system problems, particularly those drawn from the IS problem domain, may be di cult to model in crisp or precise terms. It may also be desirable that formal modelling...

Tools and techniques that have been developed during the last 40 years in the field of fuzzy set theory (FST) have been applied quite successfully in a variety of application areas. A prominent example of the practical usefulness of corresponding techniques is fuzzy control, where the idea is to represent the input-output behaviour of a controller (of a technical system) in terms of fuzzy rules...

Fuzzy systems are currently being used in a wide field of industrial and scientific applications. Therefore, it is necessary to have algorithms which construct and optimize such systems automatically. Since the idea of learning is being studied in other research areas like machine learning and data mining, some of the developed methods have been made available and optimized for the learning pro...

Data privacy has become an important topic of research. Ubiquitous databases and the eclosion of web technology eases the access to information. This information can be related to individuals, and, thus, sensitive information about users can be easily accessed by interested parties. Data privacy focuses on tools and methods to protect the privacy of the respondents and data owners. In the last ...

This paper argues that fuzzy representations are appropriate in applications where there are major sources of imprecision and/or uncertainty. Case studies of fuzzy approaches to specific problems of medical diagnosis and classification are described in support of this argument. The case studies are in the areas of categorical consistency, diagnostic monitoring and scoring. The solutions use a v...

State reduction of fuzzy automata has been studied by many authors. All of them have dealt with classical fuzzy automata over the Gödel structure and reduction has been done using crisp equivalence relations. In [2, 3, 7] we have made several innovations. We have studied fuzzy automata over a more general structure of truth values, over a complete residuated lattice, we have shown that better r...

Fuzzy sets theory is of great interest in medical image processing, for dealing with imprecise information and knowledge. It provides a consistent mathematical framework for knowledge representation, information modeling at different levels, fusion of heterogeneous information, reasoning and decision making. In this chapter, we provide an overview of the potential of this theory in medical imag...

Fuzzy PI controllers are using in the place of linear PI controller with success in process control, assuring better control quality criteria. The paper presents some methods, with a higher grade of generality, to design PI fuzzy controllers, to assure internal and external stability to control systems and better control quality criteria. Families of input-output transfer characteristics and ga...

A fuzzy regression model is used in evaluating the functional relationship between the dependent and independent variables in a fuzzy environment. Most fuzzy regression models are considered to be fuzzy outputs and parameters but non-fuzzy (crisp) inputs. In general, there are two approaches in the analysis of fuzzy regression models: linear-programmingbased methods and fuzzy least-squares meth...