Research on Electricity Customer Complaint Risk Based on Improved Grey Wolf Optimization Fuzzy C-means Clustering Algorithm
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0408-2_10
Reference11 articles.
1. Cai, D., Wang, W., Chen, K., Cao, K., et al.: Analysis on complaint behavior of electric power customers. In: 2019 IEEE Innovative Smart Grid Technologies (ISGT), Asia, pp. 3595–3600 (2019)
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3. Liu, J., Liang, B., Ji, W.: An anomaly detection approach based on hybrid differential evolution and K-means clustering in crowd intelligence. J. Crowd Sci. 5(2), 129–142 (2021)
4. Chen, Y., Zhou, L., Pei, S., Yu, Z., et al.: KNN-BLOCK DBSCAN: fast clustering for large-scale data. IEEE Trans. Syst. Man Cybern. Syst. 51(6), 3939–3953 (2021)
5. Lv, Z., Qiao, L., Cai, K., Wang, Q.: Big data analysis technology for electric vehicle networks in smart cities. IEEE Trans. Intell. Transp. Syst. 22(3), 1807–1816 (2021)
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