Wind Turbine Abnormal Data Identification Based on MKIF Model
Author:
Affiliation:
1. North China Electric Power University,School of Control and Computer Engineering,Beijing,China,102206
2. State Key Laboratory of Wind Energy Equipment and Control Technology,Beijing,China,100080
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10032843/10032844/10033963.pdf?arnumber=10033963
Reference14 articles.
1. Fuzzy C-Means-based Isolation Forest
2. K-Means-based isolation forest
3. Clustering Approach Based on Mini Batch Kmeans for Intrusion Detection System Over Big Data
4. Comparative study on detection methods of wind power abnormal data;feng;Advanced Technology of Electrical Engineering and Energy,2021
5. Wind Power Curve Data Cleaning by Image Thresholding Based on Class Uncertainty and Shape Dissimilarity
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