This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human interpretability. The algorithm uses an information theoretic approach to limit the amount of uncertainty within each decision and to determine when a rule does not effectively model the underlying decision space. Exp...

The aim of this contribution is to point out the importance of interpretability of fuzzy rule-based systems. We try to approach this key property axiomatically, as a starting point, restricting to interpretability of linguistic variables (in Zadeh’s sense). The proposed approach is underlined with an intuitive example. Finally, the benefits of considering interpretability in design and tuning o...

In natural language processing up to now mainly rule-based systems have been used. The rulebased approach has been successful for limited domains, where the manual construction of the rules is feasible. In recent studies, however, a need for automatic generation of the rules has been seen. On the other hand, when children learn their mother tongue no explicit rules seem to be needed. Therefore,...

In the last years, multi-objective genetic algorithms have been successfully applied to obtain Fuzzy Rule-Based Systems satisfying different objectives, usually different performance measures. Recently, multi-objective genetic algorithms have been also applied to improve the difficult trade-off between interpretability and accuracy of Fuzzy Rule-Based Systems, obtaining linguistic models not on...

Images of fuzzy sets under fuzzy relations have been investigated mainly in two contexts: On the one hand, mostly under the term “full image” [5], they can be regarded as very general tools for fuzzy inference, leading to the so-called “compositional rule of inference” [1, 5]. On the other hand, under the term “extensional hull”, the image of a fuzzy set under a fuzzy equivalence relation yield...

Images of fuzzy sets under fuzzy relations have been investigated mainly in two contexts: on the one hand, mostly under the term “full image” (Gottwald, 1993), they can be regarded as very general tools for fuzzy inference, leading to the so-called “compositional rule of inference” (Gottwald, 1993; Bauer et al., 1995). The theory of fuzzy relational equations makes direct use of this fundamenta...

The predicted growth in air transportation and the ambitious goal of the European Commission to have on-time performance of flights within 1 minute makes efficient and predictable ground operations at airports indispensable. Accurately predicting taxi times of arrivals and departures serves as an important key task for runway sequencing, gate assignment and ground movement itself. This research...

This paper presents an evolutionary Multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler and still accurate linguistic fuzzy models by learning fuzzy inference operators and applying rule selection. The Fuzzy Rule Based Systems obtained in this way, have a better trade-off between interpretability and accuracy in ling...

The growth of cities, climate change, biomes degradation, disease and social issues influence the views of life quality and health of populations. The characteristics of health and environment are usually measured with different and disconnected indicators. However, the importance of working with those two aspects in a joined way is every time larger. In this paper it is presented a fuzzy rule-...