Eliciting a human understandable model of ice adhesion strength for rotor blade leading edge materials from uncertain experimental data

被引：15

作者：

Palacios, Ana M. ^{[1
]}

Palacios, Jose L. ^{[2
]}

Sanchez, Luciano ^{[1
]}

机构：

[1] Univ Oviedo, Dept Informat, Gijon 33071, Asturias, Spain

[2] Penn State Univ, Dept Aerosp Engn, University Pk, PA 16802 USA

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 11期

关键词：

Genetic Fuzzy Systems; Fuzzy rule-based classifiers; Vague data; Isotropic materials; Ice-phobic materials; Shear adhesion strength; GENETIC FUZZY-SYSTEMS;

D O I：

10.1016/j.eswa.2012.02.155

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The published ice adhesion performance data of novel "ice-phobic" coatings varies significantly, and there are not reliable models of the properties of the different coatings that help the designer to choose the most appropriate material. In this paper it is proposed not to use analytical models but to learn instead a rule-based system from experimental data. The presented methodology increases the level of post-processing interpretation accuracy of experimental data obtained during the evaluation of ice-phobic materials for rotorcraft applications. Key to the success of this model is a possibilistic representation of the uncertainty in the data, combined with a fuzzy fitness-based genetic algorithm that is capable to elicit a suitable set of rules on the basis of incomplete and imprecise information. (c) 2012 Elsevier Ltd. All rights reserved.

引用

页码：10212 / 10225

页数：14