Research on association rule mining of specialty industries based on apriori algorithm

Peiguang Chen; Yong Wang; Ziheng Wang; Yiwen Jiang; Jizhe Dong

doi:10.1117/12.3018235

15 January 2024 Research on association rule mining of specialty industries based on apriori algorithm

Peiguang Chen, Yong Wang, Ziheng Wang, Yiwen Jiang, Jizhe Dong

Proceedings Volume 12983, Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023); 129832M (2024) https://doi.org/10.1117/12.3018235
Event: Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023), 2023, Wuhan, China

Abstract

With the continuous improvement of people's living standards and the intensification of electricity consumption in the whole society, rural specialty industries are facing various opportunities and challenges. This paper takes the characteristic industries of each county and city in Jilin Province as the research object, and utilizes Python to collect data and analyze the association rule mining. Firstly, this paper collects the daily electricity consumption of featured industries in each county and city in the past two years, constructs multi-dimensional datasets, and applies data mining methods to conduct data mining analysis. Secondly, we use the Apriori algorithm to analyze the association rules of the characteristic industries of each county and city under the big data of electricity. Finally, we provide useful suggestions and insights on the development of featured industries for rural revitalization through the analysis of association rules under electric power big data in each county and city.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Peiguang Chen, Yong Wang, Ziheng Wang, Yiwen Jiang, and Jizhe Dong "Research on association rule mining of specialty industries based on apriori algorithm", Proc. SPIE 12983, Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023), 129832M (15 January 2024); https://doi.org/10.1117/12.3018235

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