This paper deals with the influence of the context in fuzzy rule base systems. The linguistic variable definition of Zadeh is modified to permit context adaptation, and inference procedure is modified to handle context adaptation when evaluating fuzzy concepts. Procedures to determine context in different situations are provided. Context determination may be viewed as a kind of learning. An app...

Recognition methods use different features to assign a pattern to a prototype class. The recognition accuracy strongly depends on the selected features. In this paper we present a novel fuzzy methodology to extract appropriate fuzzy features from the handwriting data. From these meaningful features a set of linguistic rules are derived which in turn constitute a fuzzy rule base for character re...

Online group purchasing or collective purchasing is the activity in which people who desire to buy the same merchandises join together so that they can negotiate with sellers for a better price through Internet. This paper utilizes fuzzy logic to develop a bargaining model for such activities. The model supports buyers to make group decision to set up their bargaining strategy; instead of using...

In this paper we introduce a classifier named TEDAClass (Typicality and Eccentricity based Data Analytics Classifier) which is based on the recently proposed AnYa type fuzzy rule based system. Specifically, the rules of the proposed classifier are defined according to the recently proposed TEDA framework. This novel and efficient systematic methodology for data analysis is a promising addition ...

This paper presents a comparison of experimental results and a fuzzy rule based system model for calculating the cutting force in the turning operation. A full bridge dynamometer was used to measure the cutting forces over the mild steel work piece and Cemented Carbide Insert tool for different combinations of cutting velocity, feed rate and depth of cut. The rake angle, approach angle and nose...

This contribution provides an exhaustive explanation of the graded approach to the monotonicity property (of a fuzzy relation) and its non-graded version. Our framework is algebraic. We present a wide variety of examples to support our claims relating to the well defined notion and suitability for fuzzy rule base applications and moreover, to improve the readability of the following mathematica...

Credit-risk evaluation is a very challenging and important problem in the domain of financial analysis. Many classification methods have been proposed in the literature to tackle this problem. Statistical and neural network based approaches are among the most popular paradigms. However, most of these methods produce so-called ‘‘hard’’ classifiers, those generate decisions without any accompanyi...

Two main concepts are established in the literature for the Parameter Setting Problem (PSP) of metaheuristics: Parameter Tuning Strategies (PTS) and Parameter Control Strategies (PCS). While PTS result in a fixed parameter setting for a set of problem instances, PCS are incorporated into the metaheuristic and adapt parameter values according to instance-specific performance feedback. The idea o...

Although Mamdani-type fuzzy rule-based systems (FRBSs) became successfully performing clearly interpretable fuzzy models, they still have some lacks related to their accuracy when solving complex problems. A variant of these kinds of systems, which allows to perform a more accurate model representation, are the so-called approximate FRBSs. This alternative representation still cannot avoid the ...

The paper presents a generalization of the Pittsburgh approach to learn fuzzy classification rules from data. The proposed approach allows us to obtain a fuzzy rule-based system with a predefined level of compromise between its accuracy and interpretability (transparency). The application of the proposed technique to design the fuzzy rule-based classifier for the well known benchmark data sets ...