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Grid investment capability prediction based on path analysis and BP neural network
by
Liu, Huideng
, Zhu, Yuning
, Zhang, Chengke
, Wang, Yuzhu
, Hu, Zeping
in
bp neural network
/ index system
/ Indexes
/ Investment decision
/ Investments
/ Networks
/ Neural networks
/ Path analysis
/ Power
/ power grid investment capability
/ Prediction models
/ Predictions
2022
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Grid investment capability prediction based on path analysis and BP neural network
by
Liu, Huideng
, Zhu, Yuning
, Zhang, Chengke
, Wang, Yuzhu
, Hu, Zeping
in
bp neural network
/ index system
/ Indexes
/ Investment decision
/ Investments
/ Networks
/ Neural networks
/ Path analysis
/ Power
/ power grid investment capability
/ Prediction models
/ Predictions
2022
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Do you wish to request the book?
Grid investment capability prediction based on path analysis and BP neural network
by
Liu, Huideng
, Zhu, Yuning
, Zhang, Chengke
, Wang, Yuzhu
, Hu, Zeping
in
bp neural network
/ index system
/ Indexes
/ Investment decision
/ Investments
/ Networks
/ Neural networks
/ Path analysis
/ Power
/ power grid investment capability
/ Prediction models
/ Predictions
2022
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Grid investment capability prediction based on path analysis and BP neural network
Journal Article
Grid investment capability prediction based on path analysis and BP neural network
2022
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Overview
With the more complex investment environment of China’s power grid, the accurate prediction of the investment ability of power grid enterprises has become an important prerequisite for managers to make precise investment decisions. This paper first selects the factors affecting the investment capacity of the power grid from the internal and external environment, and establishes the index system of the factors affecting the investment capacity. Secondly, the path analysis is used to deeply explore the interaction relationship and influence degree of each index and investment capacity. Finally, the maximum investment capacity of the power network can be predicted based on the BP neural network prediction model. The results show that the BP neural network prediction model can achieve higher prediction accuracy when predicting the power grid investment capability.
Publisher
EDP Sciences
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