The purpose of the proposed paper is that analysis of uncertainty and impression handling in fuzzy Relational Data Base by defining the fuzzy relationships between the existing database model to Fuzzy Vague Relational Database Model (FRDBMS) with the help of fuzzy membership function for analysis of the degree of uncertain information of existing data base. Some theoretical properties of the mo...

These notes are concerned with recent developments in multivalued logic, particularly in fuzzy logic and its status as a model for human linguistic reasoning. This first section discusses the status of formal logic and the need for logics of approximate reasoning with vague data. The following sections present a hasic account of fuzzy sets theory; fuzzy logics; Zadeh's model of linguistic hedge...

– Approximate reasoning and fuzzy queries are efficient methods in retrieving information from large databases when precise attributes are unknown or the model itself is vague. We explore such types of reasoning based on the notions of the possibility theory. We suggest an approach towards a Prolog implementation of such queries which takes into account fuzzy linguistic quantification, aggregat...

Fuzzy Description Logics (fuzzy DLs) allow to describe structured knowledge with vague concepts. Unlike classical DLs, in fuzzy DLs an answer is a set of tuples ranked according to the degree they satisfy the query. In this paper, we consider fuzzy DL-Lite. We show how to compute efficiently the top-k answers of a complex query (i.e. conjunctive queries) over a huge set of instances.

Fuzzy Description Logics (DLs) are logics that allow to deal with vague structured knowledge. Although a relatively important amount of work has been carried out in the last years concerning the use of fuzzy DLs as ontology languages, the problem of automatically managing fuzzy ontologies has received no attention so far. We report here our preliminary investigation on this issue by describing ...

In this paper we consider Description Logics (DLs), which are logics for managing structured knowledge, with a well-known fuzzy extension to deal with vague information. While for fuzzy DLs ad-hoc, tableaux-like reasoning procedures have been given in the literature, the topic of this paper is to present a reasoning preserving transformation of fuzzy DLs into classical DLs. This has the conside...

The goal of this paper is to consider properties of the composition of interval-valued fuzzy relations which were introduced by L.A. Zadeh in 1975. Fuzzy set theory turned out to be a useful tool to describe situations in which the data are imprecise or vague. Interval-valued fuzzy set theory is a generalization of fuzzy set theory which was introduced also by Zadeh in 1965. This paper generali...

Some difficulties emerging during the construction of fuzzy rule bases are inherited from the type of the applied fuzzy reasoning. In fuzzy systems, when classical methods (e.g. the Compositional Rule of Inference) are applied, the completeness of the fuzzy rule base is required to generate meaningful output. This means, that the fuzzy rule base has to cover all possible inputs. The way of buil...

Vague or imprecise concepts are fundamental to natural language. Human beings are constantly using imprecise language to communicate each other. We usually say ‘John is tall and strong’ but not ‘John is exactly 1.85 meters in height and he can lift 100kg weights’. Humans have a remarkable capability to perform a wide variety of physical and mental tasks without any measurements. This capability...

In the real world, vague phenomenon is quite common in the production/inventory models. In order to process the vagueness, a production/inventory model that can be more closely related to the real vagueness and can take account of the vague factors that contribute to production costs, is required. The model must be extended or altered to fit in with the fuzzy situation. Since items with imperfe...