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...

DEA (Data Envelopment Analysis) is a technique for evaluating the relative effectiveness of decision-making units (DMU) with multiple inputs and outputs data based on non-parametric modeling using mathematical programming (including linear programming, multi-parameter programming, stochastic programming, etc.). The classical DEA methods are developed to handle the information in the form of cri...

This paper proposes a Fuzzy Dedicated Observers (FDOS) method using a Nonlinear Unknown Input Fuzzy Observer (UIFO) with a Fuzzy Scheduler Fault Tolerant Control (FSFTC) algorithm for fuzzy Takagi-Sugeno (TS) systems subject to sensor faults, parametric uncertainties, and time varying unknown inputs. FDOS provide residuals for detection and isolation of sensor faults which can affect a TS model...

In this paper, the nonlinear systems with time-varying delays and parametric uncertainties are represented by an equivalent Takagi-Sugeno type fuzzy model. Based on Convex combination property, Lyapunov criterion, and Razumikhin theorem, some sufficient conditions are derived under which the parallel-distributed fuzzy control can stabilize the whole uncertain fuzzy time-delay systems asymptotic...

In this paper, we use fuzzy rule-based classification systems for classify cells of the Eimeria of Domestic Fowl based on Morphological Data. Thirteen features were extracted of the images of the cells, these features are genetically processed for learning fuzzy rules and a method reward and punishment for tuning the weights of the fuzzy rules. The experimental results show that our classifier ...