This paper introduces a new learning methodology to quickly generate accurate and simple linguistic fuzzy models, the cooperative rules (COR) methodology. It acts on the consequent...
This paper presents an algorithm for incorporating a priori knowledge into data-driven identification of dynamic fuzzy models of the Takagi-Sugeno type. Knowledge about the modell...
A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated da...
Markos G. Tsipouras, Themis P. Exarchos, Dimitrios...
In this paper we present a new method of interval fuzzy model identification. The method combines a fuzzy identification methodology with some ideas from linear programming theory...
In the paper an application of the interval fuzzy model (INFUMO) in fault detection for nonlinear systems with uncertain intervaltype parameters is presented. A confidence band f...
In this paper we propose a generic methodology for the automated generation of fuzzy models. The methodology is realized in three stages. Initially, a crisp model is created and i...
Markos G. Tsipouras, Themis P. Exarchos, Dimitrios...
The paper considers the application of soft computing techniques for predictive modelling in the built sector. TakagiSugeno fuzzy models are built by subtractive clustering to pro...
Intelligent autonomous robots and multiagent systems, having different skills and capabilities for specific subtasks, have the potential to solve problems more efficiently and eff...
In this paper, we propose a fuzzy model to querying the XML documents, by taking into account not only the document contents, but also their structure. The concept of minimal size ...