Relations between similarity-based systems, evaluating similarity to some prototypes, and fuzzy rule-based systems, aggregating values of membership functions, are investigated. Similarity measures based on information theory and probabilistic distance functions lead to a new type of membership functions applicable to symbolic data. Fuzzy membership functions on the other hand lead to a new typ...

RNA plays a critical role in mediating every step of cellular information transfer from genes to functional proteins. Pseudoknots are functionally important and widely occurring structural motifs found in all types of RNA. Therefore predicting their structures is an important problem. In this paper, we present a new RNA pseudoknot structure prediction method based on term rewriting. The method ...

Nodes in sensor networks can be easily compromised by an adversary due to hostile environments in which compromised nodes could be used to inject false reports into the network. The dynamic en-route scheme can detect and drop such false reports during the forwarding phase. In this scheme, choosing a threshold value is important as this gives a trade off between security of power and energy cons...

Support Vector Machines (SVM) have demonstrated their ability in solving classification problems in an optimal way with a solid mathematical background. In this paper we improve the interpretability of SVM’s by showing that every SVM is exactly represented by a Fuzzy Rule BasedSystem, for every kernel function used. Nevertheless, this system is in some way compact in their rules and for that re...

In this work we consider a very general principle for fuzzy rule interpolation methods based on an interpretation of the generalized modus ponens rule in terms of closeness relations. Then we present two particular instances of the general principle when the closeness relations are defined from parametric families of similarity fuzzy relations on the input and output spaces. The case of multipl...

On this paper, an application of a high performance fuzzy logic hardware controller is explained, a model car is given autonomous character. Development of a fuzzy rule base, aided by a simulator program, is followed by trials made to come to conclusions regarding ideal and real functioning of the hardware developed.

Some difficulties emerging during the construction of fuzzy behaviour-based control structures are inherited from the type of the applied fuzzy reasoning. The fuzzy rule base requested for many classical reasoning methods needed to be complete. In case of fetching fuzzy rules directly from expert knowledge e.g. for the behaviour coordination module, the way of building a complete rule base is n...

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...

This paper proposes two kinds of fuzzy abductive inference in the framework of fuzzy rule base. The abductive inference processes described here depend on the semantic of the rule. We distinguish two classes of interpretation of a fuzzy rule, certainty generation rules and possible generation rules. In this paper we present the architecture of abductive inference in the first class of interpret...