We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, but current hill-climbing rough set approaches ...

In this paper, within the context of fuzzy rough set theory, we generalize the classical rough set framework for data-based attribute selection and reduction, based on the notion of fuzzy decision reducts. Experimental ...

A method is proposed, whereby a particular application of an operator, applied to a structure representing a Bayesian network equivalence class can be scored in a generic fashion. This is achieved by representing a particular ...

There are a variety of measures to describe classification performance with respect to different criteria and they are often represented by numerical values. Psychologists have commented that human beings can only reasonably ...

This paper presents a fuzzy knowledge-based system for turbomachinery diagnosis. Given symptoms associated with a vibration problem, the system can identify and rank possible causes by performing incremental forward chaining. ...

Fuzzy interpolative reasoning offers the potential to model problems using sparse rule bases, as opposed to dense rule bases deployed in traditional fuzzy systems. It thus supports the simplification of complex fuzzy models ...

Given a set of collected evidence and a knowledge base, Fuzzy Compositional Modelling (FCM) begins by retrieving model fragments which are the most likely to be relevant to the available data. Since FCM often involves ...

Many approaches have been developed for academic performance evaluation using various fuzzy techniques. Initial methods rely greatly on experts' specification of analytical parameters, without making use of valuable ...

Due to the explosive growth of electronically stored information, automatic methods must be developed to aid users in maintaining and using this abundance of information effectively. In particular, the sheer volume of ...