2023
doi: 10.12720/jait.14.5.892-896
Research on Substation Engineering Estimates Based on BIM-DE-RF
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Li Bian2,*
- 1Hebei Electric Power Engineering Supervision Co., Ltd, Hebei, China
- 2Shanghai Electric Power Design Institute Co., Ltd, Shanghai, China
- Manuscript receivedFebruary 6, 2023
- revisedMarch 16, 2023
- acceptedApril 11, 2023
- publishedSeptember 6, 2023
Abstract
Aiming at the problems of heavy workload and large errors in traditional substation engineering estimation methods, an intelligent estimation method for substation engineering based on Building Information Modeling (BIM) combined with a Differential Evolution (DE) algorithm to optimize Random Forest (RF) is proposed. This proposed method uses DE to optimize the RF model’s splitting features and decision trees to enhance the model’s estimation accuracy. The BIM of the substation project is used to determine engineering quantity information, which serves as the input of the DE-RF model, enabling intelligent cost estimation of the substation project. The results of the example analysis show that the relative error of the proposed cost estimation method for substation engineering based on BIM and DE-RF is below 10%. This accuracy level meets various substation engineering cost estimation scenarios, validating the feasibility and correctness of the proposed model.
Keywords
- building information modeling
- random forest
- optimization
- differential evolution
How to Cite
Songsong Wang, Wenxuan Qiao, Lei Wang, Zhewei Shen, Pengju Yang, and Li Bian, "Research on Substation Engineering Estimates Based on BIM-DE-RF," Journal of Advances in Information Technology, vol. 14, no. 5, pp. 892-896, 2023. https://doi.org/10.12720/jait.14.5.892-896
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
