Abstract
With the development of the trade and logistics industry, the calculation and analysis of big data in this industry has become a hotspot. In the field of engineering applications, the corresponding theoretical models and algorithm research results are urgently needed. This paper combines the actual cold chain logistics research project to carry out research from three aspects of storage, calculation and analysis of logistics big data. The theoretical model and key technologies are studied for logistics big data storage performance optimization and data security issues. On the basis of data storage, an effective theoretical model, strategy and key algorithms are proposed for logistics distribution calculation and shared transportation. In order to further improve the application value of logistics data analysis algorithms, distributed parallel algorithms are implemented on the basis of the original algorithms.
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Acknowledgement
Fund Project: This paper is the outcome of the study, Research on the Financing Mechanism and Countermeasures for the Innovative Development of Small and Medium-sized Enterprises, which is supported by the Foundation for Key Research Projects on Humanities and Social Sciences in Colleges and Universities of Anhui Province in 2018. The Project Number is SK2018A0865.
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Wang, J. (2020). Data Mining Method of Logistics Economy Based on Neural Network Algorithm. In: Xu, Z., Parizi, R., Hammoudeh, M., Loyola-González, O. (eds) Cyber Security Intelligence and Analytics. CSIA 2020. Advances in Intelligent Systems and Computing, vol 1146. Springer, Cham. https://doi.org/10.1007/978-3-030-43306-2_103
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DOI: https://doi.org/10.1007/978-3-030-43306-2_103
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