Some difficulties emerging during the construction of fuzzy rule bases 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, the way of building a complete rule base is not always straightforward. One simple solution for overcoming the n...

In this work we study the behaviour of a Fuzzy Rule Based Classification System, and its relationship to a certain data complexity measures family. As Fuzzy Rule Based Classification System we have selected a recent proposal called Positive Definite Fuzzy Classifier, which is a Fuzzy System that uses Support Vector Machines for its training, obtaining accurate results and a low number of rules....

this paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. then numerical results and error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. finally an example is given to illustrate the performance of the methods.

Some difficulties emerging during the construction of fuzzy behaviour-based control structures are inherited from the type of the applied fuzzy reasoning. Classical fuzzy reasoning methods need a complete fuzzy rule base. 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 not always straightforwa...

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...

In this paper, a hybrid Fuzzy Neural Network (FNN) system for function approximation is presented. The proposed FNN can handle numeric and fuzzy inputs simultaneously. The numeric inputs are fuzzified by input nodes upon presentation to the network while the Fuzzy rule based knowledge is translated directly into network architecture. The connections between input to hidden nodes represent rule ...

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...

Sensor nodes may be easily compromised and seized by adversaries, because they are disseminated in hostile environments. Adversaries may try various security attacks on sensor networks using compromised nodes. False data injection attacks using nodes may cause false alarms, and severe energy waste. The dynamic en-route filtering scheme (DEF) can detect and drop false data during the forwarding ...