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Forecasting Residential Real Estate Prices Using Deep Learning

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2024)

Abstract

For properly make decisions in the real estate market, the process of forecasting the prices of residential real estate is very important. The aim of this research is to develop a method for forecasting residential real estate prices, using deep learning. The multi-layer perceptron with Bayesian optimization has been used. The results show that the developed approach can make satisfactory predictions, close to the real values.

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Correspondence to Marcin Hernes .

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Frącz, M., Hernes, M. (2024). Forecasting Residential Real Estate Prices Using Deep Learning. In: Nguyen, N.T., et al. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2024. Communications in Computer and Information Science, vol 2145. Springer, Singapore. https://doi.org/10.1007/978-981-97-5934-7_17

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  • DOI: https://doi.org/10.1007/978-981-97-5934-7_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-5933-0

  • Online ISBN: 978-981-97-5934-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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