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- János Abonyi, Ferenc Szeifert
- Pattern Recognition Letters
- 2003

The classical fuzzy classifier consists of rules each one describing one of the classes. In this paper a new fuzzy model structure is proposed where each rule can represent more than one classes with different probabilities. The obtained classifier can be considered as an extension of the quadratic Bayes classifier that utilizes mixture of models for… (More)

- János Abonyi, Robert Babuska, Ferenc Szeifert
- IEEE Trans. Systems, Man, and Cybernetics, Part B
- 2002

The construction of interpretable Takagi-Sugeno (TS) fuzzy models by means of clustering is addressed. First, it is shown how the antecedent fuzzy sets and the corresponding consequent parameters of the TS model can be derived from clusters obtained by the Gath-Geva (GG) algorithm. To preserve the partitioning of the antecedent space, linearly transformed… (More)

- János Abonyi, Johannes A. Roubos, Ferenc Szeifert
- Int. J. Approx. Reasoning
- 2003

The data-driven identification of fuzzy rule-based classifiers for high-dimensional problems is addressed. A binary decision-tree-based initialization of fuzzy classifiers is proposed for the selection of the relevant features and effective initial partitioning of the input domains of the fuzzy system. Fuzzy classifiers have more flexible decision… (More)

- János Abonyi, Balazs Feil, Sandor Z. Németh, Peter Arva
- Fuzzy Sets and Systems
- 2005

The partitioning of a time-series into internally homogeneous segments is an important data mining problem. The changes of the variables of a multivariate time-series are usually vague and do not focus on any particular time point. Therefore it is not practical to define crisp bounds of the segments. Although fuzzy clustering algorithms are widely used to… (More)

- János Abonyi, Balazs Feil
- 2008

- Zoltán Bankó, János Abonyi
- Expert Syst. Appl.
- 2012

0957-4174/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2012.05.012 ⇑ Corresponding author. Tel.: +36 88 624209. E-mail address: abonyij@fmt.uni-pannon.hu (J. Ab In recent years, dynamic time warping (DTW) has begun to become the most widely used technique for comparison of time series data where extensive a priori knowledge is… (More)

- András Király, János Abonyi
- Intelligent Computational Optimization in…
- 2011

The Vehicle Routing Problem (VRP) is a complex combinatorial optimization problem that can be described as follows: given a fleet of vehicles with uniform capacity, a common depot, and several costumer demands; find the set of routes with overall minimum route cost which service all the demands. The multiple traveling salesman problem (mTSP) is a… (More)

- Johannes A. Roubos, Magne Setnes, János Abonyi
- Inf. Sci.
- 2003

The automatic design of fuzzy rule-based classification systems based on labeled data is considered. It is recognized that both classification performance and interpretability are of major importance and effort is made to keep the resulting rule bases small and comprehensible. For this purpose, an iterative approach for developing fuzzy classifiers is… (More)

- János Abonyi
- 2000

This paper addresses the interpretation of parameters in Takagi-Sugeno (TS) fuzzy models. The analysis is presented for the dynamic gain and steady-state representation, but it holds for parameters related to the dynamics as well. The TS model interpolates between local linear models. The overall gain obtained by interpolating the gains of the local models… (More)

- János Madár, János Abonyi, Ferenc Szeifert
- 5th International Conference on Intelligent…
- 2005

It is often desirable to simultaneously handle several objectives and constraints in practical optimization problems. In some cases, these objectives and constraints are non-commensurable and they are not explicitly/mathematically available. For this kind of problems, interactive optimization may be a good approach. Interactive optimization means that a… (More)