A Fuzzy Rule-Based Feature Construction Approach Applied to Remotely Sensed Imagery

被引：0

作者：

Garcia, David ^{[1
]}

Stavrakoudis, Dimitris ^{[2
]}

Gonzalez, Antonio ^{[1
]}

Perez, Raul ^{[1
]}

Theocharis, John B. ^{[3
]}

机构：

[1] Univ Granada, ETSIIT, Dept Computat Sci & AI, E-18071 Granada, Spain

[2] Aristotle Univ Thessaloniki, FAFNE, Sch Forestry & Nat Environm, Thessaloniki 54124, Greece

[3] Aristotle Univ Thessaloniki, Dept Elect & Comp Engn, Thessaloniki 54124, Greece

来源：

PROCEEDINGS OF THE 2015 CONFERENCE OF THE INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY | 2015年 / 89卷

关键词：

Genetic fuzzy systems; feature construction; land cover classification; remote sensing; high-dimensional classification tasks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The inherent interpretability properties of fuzzy rule-based classification systems (FRBCSs) are undoubtedly one of their major advantages when compared to conventional black-box classifiers. In this paper we present a preliminary study of how the so-called technique of feature construction can prove useful in the context of land cover classification tasks using remotely sensed imagery. The method is integrated into a previously proposed genetic FRBCS (GFRBCS) and applied in a crop classification task using a multispectral satellite image. The experimental analysis shows that feature construction can effectively identify very useful hidden relationships among the initial variables of the problem.

引用

页码：1274 / 1281

页数：8

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