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Real Estate Investment Estimation Based on BP Neural Network

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Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1303))

Abstract

Investment estimation is an important link in the feasibility study stage of residential projects. In this paper, a genetic algorithm is used to improve the BP neural network to estimate the construction and installation cost of residential construction project investment. Taking the project data of a construction company as an example, a genetic BP neural network model is constructed. Through the detection of the actual data, the error is within 10%, which meets the actual investment estimation needs.

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References

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Correspondence to Xiaochun Sun .

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Chen, Y., Cui, B., Sun, X. (2021). Real Estate Investment Estimation Based on BP Neural Network. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2020. Advances in Intelligent Systems and Computing, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-4572-0_236

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  • DOI: https://doi.org/10.1007/978-981-33-4572-0_236

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-4573-7

  • Online ISBN: 978-981-33-4572-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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