Investigating the Behaviour of Radial Basis Function Networks in Regression and Classification of Geospatial Data

被引：0

作者：

Guidali, Andrea ^{[1
]}

Binaghi, Elisabetta ^{[1
]}

Guglielmin, Mauro ^{[2
]}

Pascale, Marco ^{[1
]}

机构：

[1] Univ Insubria, Dept Comp Sci & Commun, Via Mazzini 5, I-21100 Varese, Italy

[2] Univ Insubria, Dept Structural & Funct Biol, I-21100 Varese, Italy

来源：

INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2010 | 2010年 / 6283卷

关键词：

Radial Basis Function Networks; Regression; Classification; Fuzzy sets; Geospatial data;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work investigates learning and generalisation capabilities of Radial Basis Function Networks used to solve function regression and classification tasks in the environmental context. In particular RBFN is applied to solve the problem of snow cover thickness estimation in which critical aspects such as minimal training condition, weak pattern description and inconsistency among data arise. The RBFN shows good performances and high flexibility in coping with regression, hard and soft classifications which are complementary tasks in the analysis of complex environmental phenomena.

引用

页码：110 / +

页数：2

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