Fuzzy Description Logics (DLs) generalize crisp ones by providing membership degree semantics for concepts and roles. A popular technique for reasoning in fuzzy DL ontologies is by providing a reduction to crisp DLs and then employ reasoning in the crisp DL. In this paper we adopt this approach to solve conjunctive query (CQ) answering problems for fuzzy DLs. We give reductions for Gödel, and Ł...

In this contribution we carry out an analysis of the rule weights and Fuzzy Reasoning Methods for Fuzzy Rule Based Classification Systems in the framework of imbalanced data-sets with a high imbalance degree. We analyze the behaviour of the Fuzzy Rule Based Classification Systems searching for the best configuration of rule weight and Fuzzy Reasoning Method also studying the cooperation of some...

This paper proposs a systematic methodology of fuzzy logic modeling as a generic tool for modeling of complex systems. The methodology conveys three distinct features: 1) a unified parameterized reasoning formulation; 2) an improved fuzzy clustering algorithm; and 3) an efficient strategy of selecting significant system inputs and their membership functions. The reasoning mechanism introduces f...

We review our recent works on the supersymmetrization of the leading string correction (the R term) to N = 1, 2 supergravity theories in four dimensions. We show that, in the ”old minimal” formulations of these theories, when going on-shell in the presence of this correction, the auxiliary fields which come from multiplets with physical fields cannot be eliminated, but those ones that come from...

Reasoning with propositional knowledge based on fuzzy neural logic" (1996). In this article, a new kind of reasoning for propositional knowledge, which is based on the fuzzy neural logic initialed by Teh, is introduced. A fundamental theorem is presented showing that any fuzzy neural logic network can be represented by operations: bounded sum, complement, and scalar product. Propositional calcu...

In this paper we introduce reasoning procedures for ALCQF , a fuzzy description logic with extended qualified quantification. The language allows for the definition of fuzzy quantifiers of the absolute and relative kind by means of piecewise linear functions on N and Q ∩ [0, 1] respectively. In order to reason about instances, the semantics of quantified expressions is defined based on recently...

Fuzzy extension of Description Logics (DLs) allows the formal representation and handling of fuzzy or vague knowledge. In this paper, we consider the problem of reasoning with fuzzy-EL, which is a fuzzy extension of EL+. We first identify the challenges and present revised completion classification rules for fuzzy-EL that can be handled by MapReduce programs. We then propose an algorithm for sc...

In this work we use the Choquet integral as an aggregation function and we apply it in the fuzzy reasoning method of fuzzy rule-based classification systems. We study the behaviour of several fuzzy measures and we propose a genetic learning method of an appropriate fuzzy measure to model the interaction among the set of rules of each class. In the experimental study we show that the new proposa...

In this paper, we propose a fuzzy case-based reasoning system, using a case-based reasoning (CBR) system that learns from experience to solve problems. Different from a traditional case-based reasoning system that uses crisp cases, our system works with fuzzy ones. Specifically, we change a crisp case into a fuzzy one by fuzzifying each crisp case element (feature), according to the maximum deg...

Higher order singular value decomposition (HOSVD) is an efficient datadriven decomposition technique, and shows the salient ability in the representation of high-dimensional data and feature extraction. In addition, fuzzy reasoning can solve the uncertainties of the source images’ contributions to the fused image and is easy to apply. Motivated by the advantages mentioned above, a new HOSVD and...