The present paper aims to demonstrate the interest of fuzzy inference systems in system modelling when human interaction is important. It discusses the originality of FIS and their capability to integrate expertise and rule learning from data into a single framework, analyzing their place relatively to concurrent approaches. An open source software implementation is presented, with a focus on t...

The present paper aims to demonstrate the interest of fuzzy inference systems in system modeling when human interaction is important. It discusses the originality of FIS and their capability to integrate expertise and rule learning from data into a single framework, analyzing their place relatively to concurrent approaches. An open source software implementation is presented, with a focus on th...

fuzzy logic has a high potential for managing the uncertainty sources associated with the medical expert systems. application of fuzzy inference model has been widely concentrated for managing uncertainties in computer based practices of medicine. this paper has proposed two fuzzy expert systems for prognosis of the heart disease based on: 1) mamdani inference model, and 2) sugeno inference mod...

Fuzzy-logic-based modelling and control is very efficient in dealing with imprecision and nonlinearity [1]. However, the conventional approaches for designing Fuzzy Inference Systems (FISs) are subjective, which require significant human’s efforts. Other than time consuming, the subjective approaches may not be successful if the system is too complex or uncertain. Therefore, many researchers ha...

Direct-sequence Code-division multiple-access (DS-CDMA) has emerged as proper format for communication systems. As a result of multiple-access interference (MAI), inter-symbol interference (ISI), narrowband interference (NBI) and nonlinearities in channels, DS-CDMA systems can suffer deterioration in performance . New techniques to suppress narrow-band and multiple-access interference for sprea...

In practice, the condition state of Power Transformers (PT) is quantified by using Health Index (HI). This paperanalyzes and compares three different state-of-the-art algorithms to compute HI. The first one uses a Weighted SumModel (WSM), second based on Fuzzy Inference System (FIS), third combines both techniques, i.e.,WSM FIS. These approaches are tested in PT fleet composed 30 units. Results...

The recent pandemic of COVID-19 has had severe impacts on healthcare services especially the Food and Drug Administration for providing necessary medications patients. supplier selection problem in is a crucial problem. This research aims to develop data-driven model sustainable resilient evaluation. At outset, we identify related criteria based literature experts then calculate their weights u...

some applications are critical and must designed fault tolerant system. usually voting algorithm is one of the principle elements of a fault tolerant system. two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. majority confronts with the problem of threshold limits and voter of weight...

Predicting the parameters of upcoming earthquakes has always been one most challenging topics in studies related to earthquake precursors. Increasing number sensors and satellites consequently incrementing observable possible precursors different layers lithosphere, atmosphere, ionosphere Earth opened possibility using data fusion methods estimate predict with low uncertainty. In this study, a ...

The study conducted in India using Fuzzy Inference System (FIS) is a novel approach to predicting traffic accident rates on rural highways. By various highway geometric elements as input data, the was able identify risk variables related roadway features and predict FIS. findings of suggest that FIS valuable tool for can help factors contribute accidents. also found statistically significant po...