Summary . IF-THEN rules in fuzzy inference is composed of multiple sets (membership functions). can therefore be considered as a pair membership functions [7]. The evaluation function control composite with approximate reasoning and functional on the set functions. We obtained continuity compactness [12]. Therefore, we proved existence functions, which maximizes (minimizes) rules, by using extr...

The use of hierarchical taxonomies to organise information (or sets of objects) is essential to the semantic web and is also fundamental to many aspects of web 2.0. In most cases, the seemingly crisp granulation of a taxonomy disguises the fact that categories are based on loosely defined concepts which are better modelled by allowing graded membership. Fuzzy categories may also arise when inte...

Many fuzzy clustering based techniques do not incorporate spatial relationships of the pixels, while all fuzzy rule-based image segmentation techniques tend to be very much application dependent. In most techniques, the structure of the membership functions are predefined and their parameters are either automatically or manually determined. This paper addresses the aforementioned problems by in...

Performance of a fuzzy system identifier is investigated against a fossil fuel boiler data. A multi-layer neuro-ftrzzy system presents identification of a drum type boiler. This identification techruque provides a rule-based approach to express the boiler dynamics in fuzzy rules that are generated from the experimental boiler data. The interconnections of neuro-fuzzy layers furnish these fuzzy ...

Abstrad A Fuzzijed TSK-type Recurrent Neiiral Fuzzy Network (FTRNFN) for handling furry temporal information is proposed in this paper. The inputs and oulputs of FTRNFN are fuzzy pattems represented by Gaussian or isosceles triangular membership functions. In structure, FTRNFN is a recurrent fizzy nefwork constructed from a series of recurrent fuzzy +then rules with TSK-t)pe Consequent parts. T...

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...

In this paper, we propose a novel approach to reason with spatial proximity. The approach is based on contextual information and uses a neurofuzzy classifier to handle the uncertainty aspect of proximity. Neurofuzzy systems are a combination of neural networks and fuzzy systems and incorporate the advantages of both techniques. Although fuzzy systems are focused on knowledge representation, the...

In paper industry, pulp bleaching is a most important concern in order to effectively respond to the high quality standards demanded by market requirements. Thus, a good knowledge of the bleaching plant is vital to achieve those goals. In this paper a neuro-fuzzy strategy is proposed to aid bleaching quality by predicting the outlet brightness. It consists of two phases: in the first one, a fuz...

We present a new novel method of automatically generating a multi-variable fuzzy inference system from given sample sets. We rst decompose the sample set, say , into a cluster of sample sets associated with the given input variables, then compute the associated fuzzy rules and membership functions for each variable, independent of the other variables, by solving a single input multiple outputs ...