The Use of Artifi cial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey

• Authors: Kitapci Olgun , Tosun Ömür , Tuna Murat Fatih , Turk Tarik
• Languages of publication: EN

Abstracts

EN

The purpose of this paper is to forecast housing prices in Ankara, Turkey using the artificial neural networks (ANN) approach. The data set was collected from one of the biggest real estate web pages during April 2013. A three-layer (input layer – one hidden layer – output layer) neural network is designed with 15 different inputs to forecast the future housing prices. The proposed model has a success rate of 78%. The results of this paper would help property investors and real estate agents in developing more effective property pricing management in Ankara. We believe that the artifi cial neural networks (ANN) proposed here will serve as a reference for countries that develop artifi cial neural networks (ANN) method-based housing price determination in future. Applying the artifi cial neural networks (ANN) approach for estimation of housing prices is relatively new in the field of housing economics. Moreover, this is the fi rst study that uses the artificial neural networks (ANN) approach for analyzing the housing market in Ankara/Turkey.

Keywords

EN

Housing,; artifi cial neural networks,; forecasting,; prices,; Turkey

• Publisher: Uniwersytet Warszawski. Wydział Nauk Ekonomicznych
• Journal: Journal of Marketing and Consumer Behaviour in Emerging Markets
• Year: 2017
• Issue: 1(5)
• Pages: 4-14

Dates

online

2017-03-10

Contributors

author

Kitapci Olgun

• Akdeniz University, Uygulamali Bilimler Fakultesi Department of Marketing

author

Tosun Ömür

• Akdeniz University, Uygulamali Bilimler Fakultesi Uluslararasi Ticaret ve Lojistik Bolumu

author

Tuna Murat Fatih

• Cumhuriyet University, Iktisadi ve Idari Bilimler Fakultesi Yonetim Bilisim Sistemleri Bolumu

author

Turk Tarik

• Cumhuriyet University, Muhendislik Fakultesi Geomatik Muhendisligi

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Identifiers

ISSN

2449-6634

DOI

10.7172/2449-6634.jmcbem.2017.1.1