Comprehensive evaluation of power transmission and transformation project based on electric power big data
In order to solve the problems of incomplete factors and inaccurate prediction in the current evaluation model of power transmission and transformation project, this paper uses the BP neural network algorithm optimized by simulated annealing genetic algorithm to solve the shortcomings of low trainin...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-09-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722007132 |
| Summary: | In order to solve the problems of incomplete factors and inaccurate prediction in the current evaluation model of power transmission and transformation project, this paper uses the BP neural network algorithm optimized by simulated annealing genetic algorithm to solve the shortcomings of low training efficiency and local convergence value of BP neural network in model prediction. The comparison of experimental results shows that the BP neural network optimized by simulated annealing genetic algorithm proposed in this paper is 23.21% higher than that of BP neural network. |
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| ISSN: | 2352-4847 |