Fuzzy systems address the imprecision of the input and output variables, which formally describe notions like “rather warm” or “pretty cold”, while provide a behaviour that depends on fuzzy data. This class of systems are classically represented by means of Fuzzy Inference Systems (FIS), a computing framework based on the concepts of fuzzy if-then rules and fuzzy reasoning. Even if FIS are larg...

background and objectives: surgical cancelation is a significant source of time and resource waste, patientsafety risk, and stress for patients and their families. in this study, a risk management-based approach is developed to prioritize factors contributing to surgical cancellation. methods: factors leading to surgical cancellation were comprehensively classified based on literature review.a...

This paper conducts a comparison analysis of some of the most common defuzzification techniques which helps rank fuzzy weights calculated from fuzzy comparison matrices through Fuzzy Analytic Hierarchy Process. Ranking of weights calculated through FAHP algorithms is of critical importance as it directly effects the decision making process. More so ranking of fuzzy numbers is also important in ...

in this note, we aim to present some properties of the space of all weakly fuzzy bounded linear operators, with the bag and samanta’s operator norm on felbin’s-type fuzzy normed spaces. in particular, the completeness of this space is studied. by some counterexamples, it is shown that the inverse mapping theorem and the banach-steinhaus’s theorem, are not valid for this fuzzy setting. also...

Combinational Neuro-Fuzzy (NF) logic is the mixed technique generated by the combination of artificial neural network and fuzzy-logic. Various methods are proposed in the literature to restore the image degraded by impulse noise using soft computing technique where all methods have their own advantages and disadvantages. A novel idea is proposed in this paper where the ANFIS is used to detect t...

Neuro-fuzzy systems, have recently been applied to the problem of Call Admission Control (CAC) in ATM networks. Their advantage as opposed to classical schemes, based on the modeling of sources connected to the network, is their capability to learn the behavior of data sources through training process, and to predict the future behavior based on the experience acquired in the learning process. ...

Background and aims: Depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. So, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. Use of this memory is latent in synthetic neuro-fuzzy algorithm. P...