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13 January 2023 Beijing population migration analysis based on WPD-BP neural network
Shuqi Zhang, Huiyu Zhou
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Proceedings Volume 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022); 125101K (2023) https://doi.org/10.1117/12.2656900
Event: International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 2022, Qingdao, China
Abstract
Mining the temporal pattern and migration characteristics of population flow is of great significance for the optimal allocation of national and regional human resources, the balanced development of society and economy, and the optimization of transportation systems. This paper uses wavelet packet decomposition and reconstruction to obtain the intrinsic correlation patterns of population mobility data and combines it with the BP neural network algorithm to construct the hybrid WPD-BP neural network model. The hybrid model was utilized to predict the future migration trend, and the performance results are compared with the traditional BP neural network algorithm. The empirical results show that this paper uses WPD to provide a better data set for BP neural network, and the combination of the two shows higher accuracy and lower error rate for the same data set, which confirms the feasibility and accuracy of the method. The provided method can help the regulatory authorities to better monitor the flow of people and formulate preventive and monitoring measures reasonably according to the corresponding data changes.
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Shuqi Zhang and Huiyu Zhou "Beijing population migration analysis based on WPD-BP neural network", Proc. SPIE 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 125101K (13 January 2023); https://doi.org/10.1117/12.2656900
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KEYWORDS
Neural networks
Wavelets
Evolutionary algorithms
Wavelet packet decomposition
Reconstruction algorithms
Detection and tracking algorithms
Statistical analysis
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