Application of the k-means clustering algorithm to predict load shedding of the Southern Electrical Grid of Libya
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Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/6916662/6927737/06927763.pdf?arnumber=6927763
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Unfolding self‐regulated learning profiles of students: A longitudinal study;Journal of Computer Assisted Learning;2023-06-07
2. Medium-Term Load Forecasting for The City of Benghazi Using an Artificial Neural Network Based Time Series Approach;2023 IEEE 3rd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA);2023-05-21
3. K-Means and Alternative Clustering Methods in Modern Power Systems;IEEE Access;2023
4. A Short-term Electricity Load Clustering Method Based on the Influence of the Lightning and Meteorological Factors to the Power Grid;2022 36th International Conference on Lightning Protection (ICLP);2022-10-02
5. Student Engagement Level in an e-Learning Environment: Clustering Using K-means;American Journal of Distance Education;2020-03-16
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