On-line valuation of residential premises with evolving fuzzy models

Authors:
Edwin Lughofer;Bogdan Trawiñski;Krzysztof Trawiñski;Tadeusz Lasota
Affiliations:
Johannes Kepler University Linz, Department of Knowledge-Based Mathematical Systems, Linz, Austria;Wrocław University of Technology, Institute of Informatics, Wrocław, Poland;European Centre for Soft Computing, Edificio Científico-Tecnológico, Mieres, Asturias, Spain;Wrocław University of Environmental and Life Sciences, Dept. of Spatial Management, Wroclaw, Poland
Venue:
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Year:
2011

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Abstract

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.