Fuzzy Description Logics (DLs) with t-norm semantics have been studied as a means for representing and reasoning with vague knowledge. Recent work has shown that even fairly inexpressive fuzzy DLs become undecidable for a wide variety of t-norms. We complement those results by providing a class of t-norms and an expressive fuzzy DL for which ontology consistency is linearly reducible to crisp r...

An approach based on interval belief degrees and fuzzy evidential reasoning analytical algorithm is developed for multi-criteria decision problems with uncertainties. The criteria weights are represented by interval numbers and criteria values by triangular intuitionistic fuzzy numbers. The proposed approach does not need to utilize the theories such as arithmetic operations for Triangular intu...

Case-based reasoning is a recognized paradigm and has been explored in both applied and methodological directions. In the several phases of CBR, the adaptation phase is certainly the most problematic whereas the most characteristic and interesting phase. We propose to view this task through a fuzzy analogical scheme. The adaptation is realized by focusing on the relation existing between the pr...

Fuzzy logic and case-based reasoning are leading methodologies for the application of artificial intelligence. We describe a system, WIND-1, that combines fuzzy logic and casebased reasoning to produce forecasts of airport cloud ceiling and visibility. Knowledge about meteorological and temporal features that experienced forecasters use to construct analogous climatological scenarios is encoded...

Sophisticated uncertainty representation and reasoning are necessary for the alignment and integration of Web data from different sources. For this purpose the extension of the Description Logics using fuzzy set theory has been proposed, resulting to fuzzy Description Logics (DLs). However, despite the fact that since the initial proposal a lot of work has been done in the area, the practicabil...

Spiking neural P systems (SN P systems) have been well established as a novel class of distributed parallel computing models. Some features that SN P systems possess are attractive to fault diagnosis. However, handling fuzzy diagnosis knowledge and reasoning is required for many fault diagnosis applications. The lack of ability is a major problem of existing SN P systemswhen applying them to th...

In this paper, a neural network-driven fuzzy reasoning system for stock price forecast is proposed on the basis of improved Takagi-Sugeno reasoning model. The experimental result shows that the fuzzy neural network has such properties as fast convergence, high precision and strong function approximation ability and is suitable for real stock price prediction.

The paper presents experimental comparison of several resolution strategies for reasoning in Fuzzy Description Logic based on Fuzzy Predicate Logic with evaluated syntax. Resolutionbased reasoning is established on previous works concerning non-clausal resolution principle both theoretical and application-oriented (FPLGERDS inference engine).

Simple power electronic drive circuit and fault tolerance of converter are specific advantages of SRM drives, but excessive torque ripple has limited its application. This paper presents a novel method of controlling the motor currents to minimize the torque ripple, using a neuro-fuzzy compensator. In the proposed control concept, a compensating signal is added to the output of a classical PI c...