Paper Info
Title
Investigation of bagging ensembles of genetic neural networks and fuzzy systems for real estate appraisal
Abstract
Artificial neural networks are often used to generate real appraisal models utilized in automated valuation systems. Neural networks are widely recognized as weak learners therefore are often used to create ensemble models which provide better prediction accuracy. In the paper the investigation of bagging ensembles combining genetic neural networks as well as genetic fuzzy systems is presented. The study was conducted with a newly developed system in Matlab to generate and test hybrid and multiple models of computational intelligence using different resampling methods. The results of experiments showed that genetic neural network and fuzzy systems ensembles outperformed a pairwise comparison method used by the experts to estimate the values of residential premises over majority of datasets.
Year
DOI
Venue
2011
10.1007/978-3-642-20042-7_33
ACIIDS
Keywords
Field
DocType
computational intelligence,better prediction accuracy,automated valuation system,neural network,real estate appraisal,fuzzy systems ensemble,genetic neural network,genetic fuzzy system,different resampling method,artificial neural network,bagging ensemble,ensemble models,genetics,bagging,real estate,fuzzy system
Intelligent control,Data mining,Pairwise comparison,Neuro-fuzzy,Computational intelligence,Computer science,Types of artificial neural networks,Artificial intelligence,Fuzzy control system,Artificial neural network,Machine learning,Genetic fuzzy systems
Conference
Volume
ISSN
Citations 
6592
0302-9743
19
PageRank 
References 
Authors
0.67
22
4
Name
Order
Citations
PageRank
Olgierd Kempa1442.15
Tadeusz Lasota234825.33
Zbigniew Telec317014.92
Bogdan Trawiński428824.72