Application of deep neural network in cost estimation of hydropower projects

Xin Qiu; Meiru Li; Peiyu Li; Yang Jiang; Li Peng

doi:10.1117/12.2674628

23 May 2023 Application of deep neural network in cost estimation of hydropower projects

Xin Qiu, Meiru Li, Peiyu Li, Yang Jiang, Li Peng

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260422 (2023) https://doi.org/10.1117/12.2674628
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

Investment estimation is an essential part of hydropower projects. This paper proposes a learning rate control-enabled deep learning neural network model that can be optimized for different data sizes, especially when small. Then, a DNN model with learning rate optimization is constructed based on the existing hydropower project data in China; finally, the practicality and reliability of the learning rate control enabled example calculations to verify the DNN model. According to the results, the learning rate control-enabled DNN model accurately predicts outcomes. Therefore, it can achieve accurate, fast, and adequate investment estimation for large-scale and middle-scale hydropower projects.

Citation Download Citation

Xin Qiu, Meiru Li, Peiyu Li, Yang Jiang, and Li Peng "Application of deep neural network in cost estimation of hydropower projects", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260422 (23 May 2023); https://doi.org/10.1117/12.2674628

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