نتایج جستجو برای: fuzzy membership functions

تعداد نتایج: 592303  

ژورنال: :مکانیک سازه ها و شاره ها 2012
مهدی سیاهی علیرضا الفی داوود نظری مریم آبادی محمدحسن خوبان

this paper introduces a novel control methodology based on fuzzy controller for a glucose-insulin regulatory system of type i diabetes patient. first, in order to incorporate knowledge about patient treatment, a fuzzy logic controller is employed for regulating the gains of the basis proportional-integral (pi) as a self-tuning controller. then, to overcome the key drawback of fuzzy logic contro...

2011
Ebru TURANOĞLU Eren ÖZCEYLAN Mustafa Servet KIRAN

Determination of the fuzzy membership functions in a given fuzzy logic system is the key factor for resulting in the best performance. Thus, in this study, particle swarm optimization (PSO) and artificial bee colony (ABC), relatively new member of swarm intelligence, are used to adjust the shape of fuzzy membership functions, respectively. Proposed methods have been implemented and compared for...

2012

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can...

Journal: :IJPRAI 2002
Dat Tran Michael Wagner

This paper proposes a fuzzy approach to speaker verification. For an input utterance and a claimed identity, most of the current methods compute a claimed speaker’s score, which is the ratio of the claimed speaker’s and the impostors’ likelihood functions, and compare this score with a given threshold to accept or reject this speaker. Considering the speaker verification problem based on fuzzy ...

B. Farhadinia

Recently, Gasimov and Yenilmez proposed an approach for solving two kinds of fuzzy linear programming (FLP) problems. Through the approach, each FLP problem is first defuzzified into an equivalent crisp problem which is non-linear and even non-convex. Then, the crisp problem is solved by the use of the modified subgradient method. In this paper we will have another look at the earlier defuzzifi...

Journal: :Inf. Sci. 2015
Ana M. Palacios José Luis Palacios Luciano Sánchez Jesús Alcalá-Fdez

Many methods have been proposed to mine fuzzy association rules from databases with crisp values in order to help decision-makers make good decisions and tackle new types of problems. However, most real-world problems present a certain degree of imprecision. Various studies have been proposed to mine fuzzy association rules from imprecise data but they assume that the membership functions are k...

2005
Naotoshi Sugano N. SUGANO

The present study considers 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 and output a center of gravity of three weights associated with respective grades. Triangular membership functions are applied to the hue angle, and triangular pyramid membership functions are a...

2014
Edward Hinojosa Cárdenas Heloisa de Arruda Camargo

In multi-objective evolutionary fuzzy systems, the process of tuning the membership functions plays an important role towards optimizing the systems accuracy. Although, the shape and position of the membership functions in the partition should not change too much with relation to the original partition, so that it does not lose its integrity. This paper presents and discusses multi-objective ev...

2000
Partha Chakroborty Shinya Kikuchi

The fuzzy rule based inference is known to be a useful tool to capture the behavior of an approximate system in transportation. One of the obstacles of implementing the fuzzy rule based inference, however, has been to calibrate the membership functions of the fuzzy sets used in the rules. This paper proposes a way to calibrate the membership function when a set of input and output data is given...

2001
Frank Höppner Frank Klawonn

Fuzzy clustering algorithms like the popular fuzzy cmeans algorithm (FCM) are frequently used to automatically divide up the data space into fuzzy granules (fuzzy vector quantization). In the context of fuzzy systems, in order to be intuitive and meaningful to the user, the fuzzy membership functions of the used linguistic terms have to fulfill some requirements like boundedness of support or u...

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