Research on project cost prediction of ultra-high voltage transmission lines based on RF-HKELM

Jinci Li; Yisheng Zheng; Xuanbin Hu; Ye He; Yang Zhang; Jiayu Zhao

doi:10.1117/12.3013261

29 November 2023 Research on project cost prediction of ultra-high voltage transmission lines based on RF-HKELM

Jinci Li, Yisheng Zheng, Xuanbin Hu, Ye He, Yang Zhang, Jiayu Zhao

Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 129370T (2023) https://doi.org/10.1117/12.3013261
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore

Abstract

In the context of China's increasing efforts to build extra-high voltage transmission projects, accurate and effective project cost prediction of extra-high voltage transmission lines can not only rationally arrange the investment of grid construction funds, but also effectively improve the operating conditions of power grid enterprises and guarantee the stable development of power grid enterprises. This paper takes data mining as a means to screen out the main factors affecting the cost of ultrahigh voltage transmission project, and screens the factors through random forest, takes the screened factors as inputs and the cost of engineering units as outputs, constructs a cost prediction model based on HKELM neural network, and proves the validity and applicability of the model to the investment prediction of ultra-high voltage transmission line project through empirical research, which provides an opportunity to predict the cost of ultra-high voltage transmission line project for the grid enterprises and to improve the operation of the grid enterprises. It provides a new method for the cost prediction of ultra-high voltage transmission line project.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinci Li, Yisheng Zheng, Xuanbin Hu, Ye He, Yang Zhang, and Jiayu Zhao "Research on project cost prediction of ultra-high voltage transmission lines based on RF-HKELM", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 129370T (29 November 2023); https://doi.org/10.1117/12.3013261

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