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Abstract / Description of output
Considering the complexity of the influence of the reconstruction measures for distribution network on the precision investment decision-making scheme, this paper adopts a method of data mining to establish the correlation model between the reconstruction measures and reliability evaluation indexes. In this paper, based on the sample data, the correlation mining methods of the reconstruction measures and performance indexes, including multiple linear, back propagation neural networks(BP) and recurrent neural network (RNN) methods, are applied to analyze the relationship between different types of reconstruction measures and performance indexes. Experimental result shows that the BP algorithm is more effective than the correlation model established by multiple linear regression and RNN. Meanwhile, with the increase of sample data, the accuracy of the correlation model established by BP always fluctuates within a small range. Finally, it is found that the selection of different activation functions will also have a greater impact on the accuracy of the BP correlation model.
Original language | English |
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Title of host publication | 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 3396-3400 |
Number of pages | 5 |
ISBN (Electronic) | 9781728135205 |
DOIs | |
Publication status | Published - May 2019 |
Event | 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 - Chengdu, China Duration: 21 May 2019 → 24 May 2019 |
Publication series
Name | 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 |
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Conference
Conference | 2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019 |
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Country/Territory | China |
City | Chengdu |
Period | 21/05/19 → 24/05/19 |
Keywords / Materials (for Non-textual outputs)
- BP
- Data mining
- Reliability
- RNN
- Tensorflow framework
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