LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects
The cost calculation of power transmission and transformation project is the core part of cost control technology. The quality of the cost calculation model directly affects the efficiency and reliability of the cost management of power transmission and transformation projects. However, the existing...
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2023-02-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103063 |
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| author | Xiaolin WU Ling LUAN Lianwu PAN Hailong LI |
| author_facet | Xiaolin WU Ling LUAN Lianwu PAN Hailong LI |
| author_sort | Xiaolin WU |
| collection | DOAJ |
| description | The cost calculation of power transmission and transformation project is the core part of cost control technology. The quality of the cost calculation model directly affects the efficiency and reliability of the cost management of power transmission and transformation projects. However, the existing models cannot reconcile the computational speed, accuracy and stability. Considering above-mentioned problems, firstly, a convolutional neural network model is constructed with its input and output determined according to the practical cost requirements of the power transmission and transformation projects. Then, the historical cost data are input into the network model as samples to calculate the network output. Finally, in view of the big difference between the expected output and the actual output, the Levenberg-Marquart algorithm is utilized to optimize the weight parameters of the convolutional neural network to complete the model training. Compared with the BP neural network and GD-CNN, the proposed model with higher prediction accuracy and stability combines the advantages of Levenberg-Marquart algorithm and convolutional neural network model to improve the calculation effect of power transmission and transformation project cost. |
| format | Article |
| id | doaj-art-b310789c132d4866be8bbf8d9809f5a3 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2023-02-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-b310789c132d4866be8bbf8d9809f5a32025-08-20T02:52:24ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492023-02-0156215716310.11930/j.issn.1004-9649.202103063zgdl-56-01-wuxiaolinLM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation ProjectsXiaolin WU0Ling LUAN1Lianwu PAN2Hailong LI3State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, ChinaShenyang Power Supply Company of State Grid Liaoning Electric Power Co., Ltd., Shenyang 110000, ChinaState Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, ChinaState Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, ChinaThe cost calculation of power transmission and transformation project is the core part of cost control technology. The quality of the cost calculation model directly affects the efficiency and reliability of the cost management of power transmission and transformation projects. However, the existing models cannot reconcile the computational speed, accuracy and stability. Considering above-mentioned problems, firstly, a convolutional neural network model is constructed with its input and output determined according to the practical cost requirements of the power transmission and transformation projects. Then, the historical cost data are input into the network model as samples to calculate the network output. Finally, in view of the big difference between the expected output and the actual output, the Levenberg-Marquart algorithm is utilized to optimize the weight parameters of the convolutional neural network to complete the model training. Compared with the BP neural network and GD-CNN, the proposed model with higher prediction accuracy and stability combines the advantages of Levenberg-Marquart algorithm and convolutional neural network model to improve the calculation effect of power transmission and transformation project cost.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103063power transmission and transformation projectlevenberg-marquart algorithmconvolutional neural networkautomatic calculation modelcost control |
| spellingShingle | Xiaolin WU Ling LUAN Lianwu PAN Hailong LI LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects Zhongguo dianli power transmission and transformation project levenberg-marquart algorithm convolutional neural network automatic calculation model cost control |
| title | LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects |
| title_full | LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects |
| title_fullStr | LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects |
| title_full_unstemmed | LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects |
| title_short | LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects |
| title_sort | lm cnn based automatic cost calculation model for power transmission and transformation projects |
| topic | power transmission and transformation project levenberg-marquart algorithm convolutional neural network automatic calculation model cost control |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202103063 |
| work_keys_str_mv | AT xiaolinwu lmcnnbasedautomaticcostcalculationmodelforpowertransmissionandtransformationprojects AT lingluan lmcnnbasedautomaticcostcalculationmodelforpowertransmissionandtransformationprojects AT lianwupan lmcnnbasedautomaticcostcalculationmodelforpowertransmissionandtransformationprojects AT hailongli lmcnnbasedautomaticcostcalculationmodelforpowertransmissionandtransformationprojects |