On-Line Valuation of Residential Premises with Evolving Fuzzy Models

被引：0

作者：

Lughofer, Edwin ^{[1
]}

Trawinski, Bogdan ^{[2
]}

Trawinski, Krzysztof ^{[3
]}

Lasota, Tadeusz ^{[4
]}

机构：

[1] Johannes Kepler Univ Linz, Dept Knowledge Based Math Syst, Altenbergerstr 69, A-4040 Linz, Austria

[2] Wroclaw Univ Technol, Inst Informat, PL-50370 Wroclaw, Poland

[3] Edificio Cientif Tecnolog, European Ctr Soft Comp, ES-33600 Mieres, Asturias, Spain

[4] Wroclaw Univ Enivronm & Life Sci, Dept Spatial Managem, PL-50375 Wroclaw, Poland

来源：

HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, PART I | 2011年 / 6678卷

关键词：

evolving fuzzy systems; on-line fuzzy modeling; property valuation; expert-based premise estimation; UNIVERSAL APPROXIMATORS; SYSTEMS;

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：

In this paper, we investigate on-line fuzzy modeling for predicting the prices of residential premises using the concept of evolving fuzzy models. These combine the aspects of incrementally updating the parameters and expanding the inner structure on demand with the concepts of uncertainty modeling in a possibilistic and linguistic manner (achieved through fuzzy sets and fuzzy rule bases). We use the FLEXFIS approach as learning engine for evolving fuzzy (regression) models, exploiting the Takagi-Sugeno fuzzy model architecture. The comparison with state-of-the-art expert-based premise estimation was based on a real-world data set including prices for residential premises within the years 1998 to 2008, and showed that FLEXFIS was able to outperform expert-based method.

引用

页码：107 / +

页数：3

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