A fuzzy system modeling algorithm for data analysis and approximate reasoning

被引：10

作者：

Kilic, K ^{[1
]}

Sproule, BA

Türksen, IB

Naranjo, CA

机构：

[1] Sabanci Univ, Fac Engn & Nat Sci, Istanbul, Turkey

[2] Univ Toronto, Dept Mech & Ind Engn, Toronto, ON, Canada

[3] Univ Toronto, Ctr Addict & Mental Hlth, Toronto, ON, Canada

[4] Univ Toronto, Sunnybrook & Womens Coll Hlth Sci Ctr, Psychopharmacol Res Program, Toronto, ON, Canada

[5] Univ Toronto, Fac Pharm, Toronto, ON, Canada

[6] Univ Toronto, Dept Psychiat, Toronto, ON, Canada

[7] Univ Toronto, Dept Pharmacol, Toronto, ON, Canada

[8] Univ Toronto, Dept Med, Toronto, ON, Canada

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 2004年 / 49卷 / 3-4期

基金：

英国医学研究理事会;

关键词：

fuzzy system; data analysis; approximate reasoning;

D O I：

10.1016/j.robot.2004.09.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper a new fuzzy system modeling (FSM) algorithm is introduced as a data analysis and approximate reasoning too]. The performance of the proposed algorithm is tested in two different data sets and compared with some well-known algorithms from the literature. In the comparison two benchmark data sets from the literature, namely the automobile mpg (miles per gallon) prediction and Box and Jenkins gas-furnace data are used. The comparisons demonstrated that the proposed algorithm can be successfully applied in system modeling. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：173 / 180

页数：8

共 11 条

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