نتایج جستجو برای: iterative fuzzy rule based system

تعداد نتایج: 4636528  

Journal: :CoRR 2000
Nedra Mellouli Bernadette Bouchon-Meunier

This paper proposes two kinds of fuzzy abductive inference in the framework of fuzzy rule base. The abductive inference processes described here depend on the semantic of the rule. We distinguish two classes of interpretation of a fuzzy rule, certainty generation rules and possible generation rules. In this paper we present the architecture of abductive inference in the first class of interpret...

2003
Antony Waldock Brian Carse Chris Melhuish

This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human interpretability. The algorithm uses an information theoretic approach to limit the amount of uncertainty within each decision and to determine when a rule does not effectively model the underlying decision space. Exp...

2008
Rafael Alcalá Jesús Alcalá-Fdez María José Gacto Francisco Herrera

In the last years, multi-objective genetic algorithms have been successfully applied to obtain Fuzzy Rule-Based Systems satisfying different objectives, usually different performance measures. Recently, multi-objective genetic algorithms have been also applied to improve the difficult trade-off between interpretability and accuracy of Fuzzy Rule-Based Systems, obtaining linguistic models not on...

2007
Albert Mo Kim Cheng Marko Bohanec Albert M. K. Cheng

Both crisp and fuzzy rule-based expert systems are increasingly used in the real-time environments. For both types of systems the stability and nite response time are required. It is therefore crucial for both to provide tools that perform stability analysis. This paper shows how the analysis tools built for crisp real-time rule-based system might be used for fuzzy systems as well. Major diiere...

ژورنال: طب کار 2016
درهمی, ولی, زارع, محمدجواد, سرباز عقدائی, فاطمه, سلطانی گردفرامرزی, رضیه, مستغاثی, مهرداد, موسوی, مریم,

Introduction: Diagnosis of various diseases in medicine is one of the area's most widely used data mining in recent years and many researches have been done about it. In this study, the diagnosis of prostate cancer using fuzzy system was assessed. The goal was to diagnose the prostate cancer and to predict the possibility of suffering from the disease. Methods: In the proposed method, at fir...

2012
H. Shayeghi H. A. Shayanfar O. Abedinia

This paper addresses a robust fuzzy controller to damp low frequency oscillation following disturbances in power systems. In this research the fuzzy controller is used as a Power System Stabilizer (PSS) to improve the stability in power system. The rule base of the proposed PSS is optimized offline automatically by the improved Genetic Algorithm (GA). Usually in a rule base fuzzy control system...

Journal: :iranian journal of optimization 2009
s.h. nasseri h. attari

in this paper, chebyshev acceleration technique is used to solve the fuzzy linear system (fls). this method is discussed in details and followed by summary of some other acceleration techniques. moreover, we show that in some situations that the methods such as jacobi, gauss-sidel, sor and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrate...

2014
Idris Mala Pervez Akhtar Tariq Javid Ali Syed Saood Zia

A fuzzy rule-based system design concentrates on accuracy and interpretability of the system. Fuzzy decision tree method is proposed based on fuzzy RDBMS and rule generation based on C4.5 algorithm known as fuzzy rule generation system (FRGS) algorithm. A fuzzy decision tree is developed by first converting a medical application of heart relational database to fuzzy heart relational database an...

1996
Chantana Chantrapornchai Sissades Tongsima Edwin H.-M. Sha

In a large fuzzy rule-based system, a great dealof computation time is required for a fuzzy inference engine. A given fuzzy rule-based system is modeled as a fuzzy inference graph where each node in the graph corresponds to a relation representing a rule in the rule-based system. This paper presents algorithms to minimize the number of nodes in the graph using fuzzy operations as well as their ...

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