Data Mining Method of Logistics Economy Based on Neural Network Algorithm
- 17 Downloads
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.
KeywordsData mining Neural network algorithm Logistics economy
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.
- 1.Dalvi, P.K., Khandge, S.K., Deomore, A., et al.: Analysis of customer churn prediction in telecom industry using decision trees and logistic regression. In: 2016 Symposium on Colossal Data Analysis and Networking (CDAN), pp. 1–4. IEEE (2016)Google Scholar
- 3.Montenegro, C., Segura, M., Loza-Aguirre, E.: Identifying the orientations of sustainable supply chain research using data mining techniques: contributions and new developments. In: International Conference on Software Process Improvement, pp. 121–131. Springer, Cham (2018)Google Scholar
- 4.Weerasinghe, K., Wijegunasekara, M.C.: A comparative study of data mining algorithms in the prediction of auto insurance claims. Eur. Int. J. Sci. Technol. 5(1), 47–54 (2016)Google Scholar
- 7.Zhang, H., Zhang, L., Cheng, X., et al.: A novel precision marketing model based on telecom big data analysis for luxury cars. In: 2016 16th International Symposium on Communications and Information Technologies (ISCIT), pp. 307–311. IEEE (2016)Google Scholar
- 8.Zhou, Q., Thai, V.V.: Application of data-mining techniques for personal injury evaluation in tanker shipping industry. Int. J. Comput. Commun. Instrum. 2(2), 185–190 (2015)Google Scholar
- 10.Mao-Ran, Z., Wei, F., Yuan, S.: The research of SME financial crisis warning model based on neural network. DEStech Trans. Econ. Bus. Manag., 120–128 (2016). (ICEME-EBM)Google Scholar
- 11.Massaro, A., Maritati, V., Galiano, A., et al.: ESB platform integrating KNIME data mining tool oriented on Industry 40 based on artificial neural network predictive maintenance. Int. J. Artif. Intell. Appl. 9, 1–17 (2018)Google Scholar