scholarly journals Research and application progress of data mining technology in electric power system

2021 ◽  
Vol 1 (1) ◽  
pp. 21-30
Author(s):  
Fangwei NING ◽  
Yan SHI ◽  
Yishu CAI ◽  
Weiqing XU
2013 ◽  
Vol 340 ◽  
pp. 1050-1054
Author(s):  
Chun Zhao Zhou ◽  
Yan Yan ◽  
Hao Zhang ◽  
Chao Wang ◽  
Liang Wang

This project applies Data Mining technology to the prediction of electric power system load forecast. It proposes a mining program of electric power load forecasting data based on the similarity of time series research, in the method, the average of each segment of time-sequence load is used to reduce the dimension of the problem. The similarity inquiring of each sub-sequence of loads is realized by using slipping window and MBR method. The inquiring is improved in efficiency by designing the index structure according to the-tree. Effectively overcome the negative effects on the prediction results caused by the limited and incomplete data. It also illustrates a list of examples to prove that the conducted method is effective and efficient.


2016 ◽  
Vol 2016 (4) ◽  
pp. 68-70 ◽  
Author(s):  
P. Chernenko ◽  
◽  
O. Martyniuk ◽  
V. Miroshnyk ◽  
◽  
...  

2018 ◽  
Vol 138 (6) ◽  
pp. 412-415 ◽  
Author(s):  
Ryo Maeda ◽  
Takeshi Fukuoka ◽  
Yasutoshi Yoshioka ◽  
Atsushi Harada

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