This paper shows how a small number of linguistically interpretable fuzzy rules can be extracted from numerical data for high-dimensional pattern classi®cation problems. One diculty in the handling of high-dimensional problems by fuzzy rule-based systems is the exponential increase in the number of fuzzy rules with the number of input variables. Another diculty is the deterioration in the com...

In the field of classification problems, we often encounter classes with a very different percentage of patterns between them, classes with a high pattern percentage and classes with a low pattern percentage. These problems receive the name of “classification problemswith imbalanced data-sets”. In this paperwe study the behaviour of fuzzy rule based classification systems in the framework of im...

Both crisp and fuzzy rule-based expert systems are increasingly used in the real-time environments. For both types of systems the stability and nite response time are required. It is therefore crucial for both to provide tools that perform stability analysis. This paper shows how the analysis tools built for crisp real-time rule-based system might be used for fuzzy systems as well. Major diiere...

Evolving Takagi-Sugeno (eTS) fuzzy models are used to build a computational model for the WasteWater Treatment Plant (WWTP) in a paper mill. The fuzzy rule base is constructed on-line from data using a recursive fuzzy clustering algorithm that develops the model structure and parameters. In order to avoid some redundancy in the fuzzy rule base mechanisms for merging membership functions and sim...

This paper presents an automatic learning algorithm which generates a fuzzy rule based knowledge representation. While learning the membership functions and rules the internal structure of the rule base is also considered. This is done by definition of 1 a complexity cost function and 2 a minimal Fuzzy System. A Genetic Algorithm is used to estimate the Fuzzy Systems which capture a low comlex ...

This paper briefly elaborates on a development in (applied) fuzzy logic that has taken place in the last couple of decades, namely, the complementation or even replacement of the traditional knowledge-based approach to fuzzy rule-based systems design by a data-driven one. It is argued that the classical rule-based modeling paradigm is actually more amenable to the knowledge-based approach, for ...