Data-driven fuzzy modeling has been used in a wide variety of applications. However, in fuzzy rule-based models acquired from numerical data, redundancy often exists in the form of redundant rules or similar fuzzy sets. This results in unnecessary structural complexity and decreases the interpretability of the system. In this paper, a rule-base self-extraction and simpli&cation method is propos...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

The main aim of this paper is to present MOGUL, a Methodology to Obtain Genetic fuzzy rule-based systems Under the iterative rule Learning approach. MOGUL will consist of some design guidelines that allow us to obtain diierent Genetic Fuzzy Rule-Based Systems, i. e., evolutionary algorithm-based processes to automatically design Fuzzy Rule-Based Systems by learning and/or tuning the Fuzzy Rule ...

Economic modeling of financial markets attempts to model highly complex systems in which expectations can be among the dominant driving forces. It is necessary, then, to focus on how agents form expectations. We believe that they look for patterns, hypothesize, try, make mistakes, learn and adapt. Agents’ bounded rationality leads us to a rule-based approach which we model using Fuzzy Rule Base...

Over the last years fuzzy control has become a very popular and successful control paradigm. The basic idea of fuzzy control is to incorporate human expert knowledge. This expert knowledge is speciied in a rule based manner on a high and granular level of abstraction. By using vague predicates a fuzzy rule base neglects useless details and concentrates on important relations. Following L.A. Zad...

F TP (Fuzzy Template Predicate) is proposed as a template to incorporate concept-based match into fuzzy production languages. A thesaurus augmented in F TP supports the concept-based match, which is more sophisticated than previous fuzzy match mechanisms. Membership functions for fuzzy linguistic variables and fuzzy numbers are used as an interface to the thesaurus. F TP also has self reening f...

In this work we study the behaviour of a Fuzzy Rule Based Classification System, and its relationship to a certain data complexity measures family. As Fuzzy Rule Based Classification System we have selected a recent proposal called Positive Definite Fuzzy Classifier, which is a Fuzzy System that uses Support Vector Machines for its training, obtaining accurate results and a low number of rules....

Economic modelling of financial markets means to model highly complex systems in which expectations can be the dominant driving forces. Therefore it is necessary to focus on how agents form their expectations. We believe that they look for patterns, hypothesize, try, make mistakes, learn and adapt. Agents’ bounded rationality leads us to a rule-based approach which we model using Fuzzy Rule-Bas...

In this paper, we study fuzzy calculus in two main branches differential and integral.  Some rules for finding limit and $gH$-derivative of $gH$-difference, constant multiple of two fuzzy-valued functions are obtained and we also present fuzzy chain rule for calculating  $gH$-derivative of a composite function.  Two techniques namely,  Leibniz's rule and integration by parts are introduced for ...

Fuzzy technology became a very important controlling method in complex systems where traditional methods are unsuccessful. It was proved in [19] that fuzzy rule systems can be used as general approximators of any complex continuous systems. The key element of the approximation process is the construction of the corresponding fuzzy rule system that encapsulates the knowledge on the problem domai...