BACKGROUND Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis. METHODS In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical di...

The aim of this study is to define a fuzzy based prediction system, that will accept the patient basic information as well as the symptoms as input and identify the chances of heart disease. The fuzzy based system is defined on multiple parameters based on which the patient disease analysis can be performed. The parameters taken in this work are Patient Age, Blood Pressure, Cholesterol Level an...

An efficient technique that integrates the advantages of both fuzzy theory and Hopfield type neural network for object extraction from noisy background is proposed in this article. In the initial phase of the proposed technique, a fuzzy contrast enhancement of the input noisy object scene is carried out. Subsequently, the object scene is thresholded based on its fuzzy cardinality values to gene...

A learning algorithm based on a fuzzy δ rule is proposed for a fuzzy perceptron with the same topological structure as conventional linear perceptrons. The inner operations involved in the working process of this fuzzy perceptron are based on the max-min logical operations rather than conventional multiplication and summation etc. The initial values of the network weights are fixed as 1. Each v...

The synthesis of a control system includes both the controller selection and the adjustment of its parameters. In some cases, the type of controller might be more complex or more general, like PID instead PI or PD, to improve the control system performance. In all cases, the tuning problem must be satisfactorily solved. On the other hand, Fuzzy Control has made possible the establishment of int...

This research applied fuzzy c-means and fuzzy integral theories to a proposed novel two-step machinery fault diagnosis model. Distributed multiple fuzzy c-means classifiers were used to produce an initial diagnosis result by considering different features. Fuzzy measure and fuzzy integral data fusion theory was then applied to combine the initial diagnosis results into a consensus final decisio...

--------------------------------------------------------------------ABSTRACT-----------------------------------------------------------------The fuzzy logic and expert system is an important technique to enhance the machine learning reasoning. In this paper, we propose a fuzzy expert system framework which constructs large scale knowledge based system effectively for diabetes. The knowledge is ...

Sometimes we have to work with  $L$-fuzzy context sequences where one or more values are missing. These sequences can represent, among other things, the evolution in time of an $L$-fuzzy context. The studies of tendencies that we have done so far used tools that are not valid when the $L$-fuzzy context has unknown values. In this work we address such situations and we propose new methods to tac...

An adaptive fuzzy gain scheduling scheme for robotic arm has been proposed. This paper focus on adaptive fuzzy based tracking and gain controller algorithm for obtaining the joints position relative to the desired trajectory, which drives static and different time variations on the environmental changes. We able to estimate them at any point of time, when t >0 or alternatively, starting from th...