Spatial information for coastal risk assessment is inherently uncertain. This uncertainty may be due to different spatial and temporal components of geospatial data and to their semantics. The spatial uncertainty can be expressed either quantitatively or qualitatively. Spatial uncertainty in coastal risk assessment itself arises from poor spatial representation of risk zones. Indeed, coastal ri...

This paper introduces a new software product FuzzME. It was developed as a tool for creating fuzzy models of multiple-criteria evaluation and decision making. The type of evaluations employed in the fuzzy models fully corresponds with the paradigm of the fuzzy set theory; the evaluations express the (fuzzy) degrees of fulfillment of corresponding goals. The FuzzME software takes advantage of li...

In this paper the author presents a kind of Soft Computing Technique, mainly an application of fuzzy set theory of Prof. Zadeh [16], on a problem of Medical Experts Systems. The choosen problem is on design of a physician’s decision model which can take crisp as well as fuzzy data as input, unlike the traditional models. The author presents a mathematical model based on fuzzy set theory for phy...

We introduce in this paper a quantitative preference based argumentation system relying on ASPIC argumentation framework and fuzzy set theory. The knowledge base is fuzzified to allow the experts to express their expertise (premises and rules) attached with grades of importance in the unit interval. Arguments are attached with a score aggregating the importance expressed on their premises and r...

This model for fuzzy rough sets is one of the most important parts in rough set theory. Moreover, it is based on an equivalence relation (indiscernibility relation). However, many systems are not only concerned with fuzzy sets, but also based on a dominance relation because of various factors in practice. To acquire knowledge from the systems, construction of model for fuzzy rough sets based on...

Process capability indices (PCIs) provide numerical measures on whether a process confirms to the defined capability prerequisite. They have been used to measure the ability of process to decide how well the process meets the specification limits (SLs). The PCIs have been successfully applied by companies for evaluating the quality and productivity performance. In this paper, one of the most im...

To avoid self-contradictions in Fuzzy Set Theory, it is needed to consider only fuzzy sets that are not selfcontradictory and whose complements are also not selfcontradictory. This paper deals with a subset Fnc(E) in [0, 1] , where the above conditions are satisfied. A particular Fuzzy Set Theory is defined in Fnc(E) with adequate logical connectives. Finally, which classical properties hold in...

In spite of its successes as a tool in the field of engineering, fuzzy set theory has yet to achieve the universal footing that probability theory has across the various fields of mathematics, technology, philosophy and psychology. This paper sets out points of critique brought up regarding the fuzzy approach and seeks to analyze them, focusing on the question of whether anything that can be do...

The concept of quasi-coincidence of a fuzzy interval value with an interval valued fuzzy set is considered. In fact, this is a generalization of quasi-coincidence of a fuzzy point with a fuzzy set. By using this new idea, the notion of interval valued (∈,∈ ∨q)-fuzzy filters in BL-algebras which is a generalization of fuzzy filters of BL-algebras, is defined, and related properties are investiga...

This paper presents a modeling approach which couples fuzzy object-oriented database modeling with fuzzy logic. The modeling approach introduced here handles fuzziness at attribute, object/class and class/superclass levels in addition to fuzziness in class/class relationships and various associations among classes. We utilize logical rules to define some of the crisp/fuzzy relationships and ass...