Data-driven prediction model and performance analysis based on optimized neural network

Xi He; Qicheng Xu; Xilong Li

doi:10.1117/12.3012484

21 December 2023 Data-driven prediction model and performance analysis based on optimized neural network

Xi He, Qicheng Xu, Xilong Li

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 1297040 (2023) https://doi.org/10.1117/12.3012484
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

This paper studies the prediction and performance comparison based on BP, PSO-BP and SA-BP models. Taking real estate as an example, because of the complex and nonlinear relationship between its influencing factors, the accuracy of traditional prediction methods is low. Therefore, this paper proposes an innovative prediction model based on SA-BP neural network, and verifies its effectiveness through 110 sets of real estate transaction data in Shenyang from 2021 to 2022. The experimental results show that the prediction accuracy of PSO-BP and SA-BP models is better than that of BP model, and SA-BP model performs best. This study fills the research gap in related fields and provides valuable reference for market decision-making such as real estate.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xi He, Qicheng Xu, and Xilong Li "Data-driven prediction model and performance analysis based on optimized neural network", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 1297040 (21 December 2023); https://doi.org/10.1117/12.3012484

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