Hesitant fuzzy linguistic term sets were introduced to grasp the uncertainty existing in human reasoning. In this paper, inspired by absolute order-of-magnitude qualitative reasoning techniques, an extension of the set of hesitant fuzzy linguistic term sets is presented to capture differences between non-compatible preferences. In addition, an order relation and two closed operations over this ...

Fuzzy relations are simple mathematical structures that enable a very general representation of fuzzy knowledge, and fuzzy relational calculus offers a powerful machinery for approximate reasoning. However, one of the most relevant limitations of approximate reasoning is the efficiency bottleneck. In this paper, we present a module for fast fuzzy inference through relational composition, with t...

Simple power electronic drive circuit and fault tolerance of converter are specific advantages of SRM drives, but excessive torque ripple has limited their use to special applications. It is well known that controlling the current shape adequately can minimize the torque ripple. This paper presents a new method for shaping the motor currents to minimize the torque ripple, using a neuro-fuzzy co...

The Disjunctive Fuzzy Temporal Constraint Network (DFTCN) model is a framework that allows reasoning with fuzzy qualitative and quantitative complex temporal constraints. However, its general complexity is exponential. In this work, we review methods that can reduce this complexity, based on graph topology and preprocessing. The final goal is to integrate all these methods into a general tool f...

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

In this research, a hybrid approach by combining Self-Organizing Map (SOM) and Evolving Fuzzy Case-Based Reasoning (EFCBR) for flow time prediction is proposed. Genetic Algorithms (GAs) is applied to fine-tune the fuzzy term numbers and weights of fuzzy features in the CBR model. The flow time and related shop floor status are collected and fed into the SOM for classification. Then, correspondi...

Since its introduction in the mid-sixties (Zadeh, L. A., (1965)), fuzzy set theory has gained recognition in a number of fields in the cases of uncertain, or qualitative or linguistically described system parameters or processes based on approximate reasoning, and has proven suitable and applicable with system describing rules of similar characteristics. It can be successfully applied with nume...

CFNN hybrid system in Multi-sensor data fusion introduced fuzzy logic reasoning and neural network adaptive, self-learning ability, and using fuzzy neurons, so networking skills appropriate to adjust the input and output fuzzy membership function, and can dynamically optimize fuzzy reasoning in global by means of compensated logic algorithm, to make the network more fault tolerance, stability a...

In this paper we describe a fuzzy Description Logic reasoner which implements resolution in order to provide reasoning services for expressive fuzzy DLs. The main innovation of this implementation is the ability to reason over assertions with abstract (unspecified) fuzzy degrees. The answer to queries is, consequently, an algebraic expression involving the (unknown) fuzzy degrees and the degree...

A variety of fuzzy description logics are proposed to extend classical description logics with fuzzy capability. However, reasoning with general TBoxes is still an open problem in fuzzy description logics. In this paper, we present a novel discrete tableau algorithm for a given fuzzy description logic FSHI with general TBoxes, which tries to construct discrete tableaus of FSHI knowledge bases. ...