نتایج جستجو برای: interval type 2 fuzzy logic systems

تعداد نتایج: 4649030  

Journal: :Soft Comput. 2008
Yu Qiu Hong Yang Yanqing Zhang Yichuan Zhao

In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system (FLS). In order to make the type-2 FLS reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and probability type reduce reasoning method for the interval-valued FLS are developed. We have...

2005
Janusz T. Starczewski

So far, computational complextity of the general formula for the extended t-norm does not allow to construct fuzzy logic systems of type-2 other than interval type. In this paper, we derive new formulae for extended t-norms for arguments with Gaussian and piecewise-Gaussian membership functions basing on our original theorems.

Liangliang Dai Na Hu Yanbing Gong

This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuz...

ژورنال: پیاورد سلامت 2017
خواجه پور, حسن, خواجه پور, عصمت, سالاری, راحله, لنگری زاده, مصطفی,

Background and Aim: Bacterial meningitis detection is a complicated problem because of having several components in order to be diagnosed and distinguished from other types of meningitis. Fuzzy logic and neural network, frequently used in expert systems, are able to distinguish such diseases. The purpose of this paper is to compare Fuzzy logic and artificial neural networks for distinguishing b...

2017
Arturo Tellez Heron Molina Luis Villa Elsa Rubio Ildar Batyrshin

Journal: :IJFSA 2012
Ahmad Taher Azar

Fuzzy set theory has been proposed as a means for modeling the vagueness in complex systems. Fuzzy systems usually employ type-1 fuzzy sets, representing uncertainty by numbers in the range [0, 1]. Despite commercial success of fuzzy logic, a type-1 fuzzy set (T1FS) does not capture uncertainty in its manifestations when it arises from vagueness in the shape of the membership function. Such unc...

2007
E. Jammeh M. Fleury C. Wagner H. Hagras M. Ghanbari

Intelligent congestion control is vital in encoded video streaming of a clip or film, as network traffic volatility requires constant adjustment of the bit-rate. Equation-based solutions to congestion control are prone to fluctuations in the delivery rate and may respond only when packet loss has already occurred, while both fluctuations and packet loss affect the end-user’s perception of the d...

2017
R. Saranya

In this paper an Interval Type2 Fuzzy Logic (IT2FL) controller is proposed for the control of DC-DC converters to attain a good output voltage regulation and dynamic response. The buck and boost type DC-DC converters are considered for the implementation of the IT2FL controller. To study the effects on the system performance, the conventional PI and type-1 fuzzy controller are designed and comp...

2013
Nesrine Baklouti Robert John Adel M. Alimi

Navigation of autonomous mobile robots in dynamic and unknown environments needs to take into account different kinds of uncertainties. Type-1 fuzzy logic research has been largely used in the control of mobile robots. However, type-1 fuzzy control presents limitations in handling those uncertainties as it uses precise fuzzy sets. Indeed type-1 fuzzy sets cannot deal with linguistic and numeric...

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