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...

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 ...

In this paper we propose an evolutionary learning based fuzzy theoretic approach for classifying video sequences into generic categories. This categorization is based on video structure based syntactic features. The features like shot durations, editing style, camera work and shot activity conveys large amount of information about the type of video. The information derived from these features i...

In most control and engineering applications, the use of fuzzy system as a way to improve the humtzn-computer interaction has becoming popular. This paper reports on the use of fuzzy system in mineral processing specifically in determining the parameter d50c of hydrocyclone. However, wit,h the inputoutput data provided to build the fuzzy rule base, it normally results in a sparse fuzzy rule bas...

This paper shows the use of Fingrams –Fuzzy Inference-grams– aimed at unveiling graphically some hidden details in the usual behavior of the precise fuzzy modeling algorithm FURIA –Fuzzy Unordered Rule Induction Algorithm–. FURIA is recognized as one of the most outstanding fuzzy rule-based classification methods attending to accuracy. Although FURIA usually produces compact rule bases, with lo...

Support vector machines (SVMs) proved to be highly efficient computational tools in various classification tasks. However, SVMs are nonlinear classifiers and the knowledge learned by an SVM is encoded in a long list of parameter values, making it difficult to comprehend what the SVM is actually computing. We show that certain types of SVMs are mathematically equivalent to a specific fuzzy–rule ...

This paper presents the rule-based multi-agent system MAGSY. The kernel of an agent in MAGSY is a forward-chaining rule interpreter. Therefore, each agent has the problem solving capacity of an expert system. Each agent in MAGSY is a self-contained entity with a unique identiication. If an agent knows the identiication of another agent, it is able to send this agent messages. In doing so the ag...

A new image retrieval system based on association rule (ARIRS) is described in this paper. Association rules have been used in application such as market basket analysis to capture relationships presented among items in large data sets. It is shown that association rules are able to find the frequent item pairs. In the image retrieval system, user’s interaction is a very important part. But it ...