In this paper a fraud detection method is proposed which user behaviors are modeled using two main components namely the un-normal trend analysis component and scenario based component. The extent of deviation of a transaction from his/her normal behavior is estimated using fuzzy membership functions. The results of applying all membership functions on a transaction will then be infused and a f...

The elicitation method of the fuzzy membership function depends on the interpretation of the membership function. This paper applies a recently developed neural network framework, Plausible Neural Network (PNN), to generate fuzzy membership functions automatically with or without class labeling based on the similarity and likelihood measurement. The approach combining supervised and unsupervise...

AbsrractConventional fuzzy logic controller uses input membership functions that consist of identical triangular input membership functions (MF) for all the subsets that are not located at the two ends of the universal set (center width constant or CWC). Some researchers in the field of motor controllers have started using narrower base triangular membership functions for the input subsets that...

This paper proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS) for predicting the surface roughness in turning operation for set of given cutting parameters, namely cutting speed, feed rate and depth of cut. Two different membership functions, triangular and bell shaped, were adopted during the training process of ANFIS in order to compare the prediction accuracy of surface roughness by t...

The shapes of terms used in fuzzy systems have adopted several ‘conventions’. Terms are almost invariably normalised (having a maximum membership value of 1), convex (having a single maximum or plateau maxima) and distinct (being restricted in their degree of overlap: often expressed as some variation on the concept that all membership values at any point in the universe of discourse sum to 1 a...

In this dissertation the generation and tuning of fuzzy membership function parameters are considered as a part of the fuzzy model development process. The automatic generation and tuning of fuzzy membership function parameters are needed for the fast adaptation and tuning of fuzzy models of various nonlinear dynamical systems. The developed methods are especially useful in automatic fuzzy memb...

Predicting air pollution is an important prerequisite for estimating, monitoring and mapping unknown pollution values. We can use fuzzy spatial prediction techniques to determine pollution concentration areas in practical situations where our observations are imprecise and vague. Fuzzy membership kriging with a semi-statistical membership function is an example of this type of technique. The im...

The present study considered a fuzzy natural color system (NCS) in which triangular pyramid membership functions are constructed on the NCS color triangle. This system can process a fuzzy input to an NCS system and output to a center of gravity of three weights associated with respective grades. Triangular membership functions are applied to the hue, and triangular pyramid membership functions ...

Given a fuzzy logic system, how can we determine the membership functions that will result in the best performance? If we constrain the membership functions to a certain shape (e.g., triangles or trapezoids) then each membership function can be parameterized by a small number of variables and the membership optimization problem can be reduced to a parameter optimization problem. This is the app...