The analysis of data complexity is a proper framework to characterize the tackled classification problem and to identify domains of competence of classifiers. As a practical outcome of this framework, the proposed data complexity measures may facilitate the choice of a classifier for a given problem. The aim of this paper is to study the behaviour of a fuzzy rule based classification system and...

We introduce a fuzzy controller which uses a fuzzy rule base diierently to the classical Mamdani approach. We argue that it has several desirable and well-motivated properties which often cannot be obtained by a Mamdani controller. Let X and Y denote the input and the output space, respectively, and let F(:) denote the collection of all fuzzy subsets. The support of a fuzzy set A 2 F(X) is Supp...

The determination of transformer fault categories using soft-computing based techniques has been the subject of much research in the recent past. The development of an adaptive fuzzy classifier which can effectively determine various classes or categories of series and shunt impulse faults in a wide range of power transformers is described. The system employs a self-generating module to automat...

This paper presents a design method for fuzzy rule-based systems that performs data modeling consistently according to the symbolic relations expressed by the rules. The focus of the model is the interpretability of the rules and the model’s accuracy, such that it can be used as tool for data understanding. The number of rules is defined by the eigenstructure analysis of the similarity matrix, ...

Article history: Available online 4 March 2011

We propose a fuzzy rule-based system to map representations of the emotional state of an animated agent onto muscle contraction values for the appropriate facial expressions. Our implementation pays special attention to the way in which continuous changes in the intensity of emotions can be displayed smoothly on the graphical face. The rule system we have defined implements the patterns describ...

1 Dental Diagnosis from X-Ray Images using Fuzzy Rule-Based Systems; Tran Manh Tuan, School of Information and Communication Technology, Thai Nguyen University, Thai Nguyen, Vietnam Nguyen Thanh Duc, Hanoi University of Science and Technology, Hanoi, Vietnam Pham Van Hai, Hanoi University of Science and Technology, Hanoi, Vietnam Le Hoang Son, VNU University of Science, Vietnam National Univers...

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produ...

Previously we proposed a scheme to generate fuzzy rule-based multiclassification systems by means of bagging, mutual information-based feature selection, and a multicriteria genetic algorithm (GA) for static component classifier selection guided by the ensemble training error. In the current contribution we extend the latter component by the use of two bi-criteria fitness functions, combining t...

In this paper, we evaluate and contrast two fuzzy classifiers for credit scoring. The first classifier uses evolutionary optimisation and boosting whereas the second classifier is based on a fuzzy neural network. We show that, for the case at hand, the boosted genetic fuzzy classifier performs better than both the neurofuzzy classifier and the well-known C4.5 algorithm that we included as a ref...