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  • Open Access

    ARTICLE

    Research on Substation Siting Based on a 3D GIS Platform and an Improved BP Neural Network

    Yao Jin1,2,*, Jie Zhao1,2, Xiaozhe Tan1,2, Linghou Miao1,2, Wenxing Yu1,2

    Digital Engineering and Digital Twin, Vol.2, pp. 131-144, 2024, DOI:10.32604/dedt.2024.048142 - 31 December 2024

    Abstract Substation siting is an important foundation and a key task in power system planning. The article is based on a three-dimensional GIS platform combined with an improved BP neural network algorithm and proposes a substation siting method that is more efficient, accurate and provides a better user experience. Firstly, the BP algorithm is enhanced to improve its convergence speed and computational efficiency for a more accurate and reasonable calculation of optimal site selection. Then, a 24-item selection index system with 7 categories is proposed, which provides quantifiable data support and an evaluation basis for substation… More >

  • Open Access

    ARTICLE

    Prediction of the Slope Solute Loss Based on BP Neural Network

    Xiaona Zhang1,*, Jie Feng2, Zhiguo Yu1, Zhen Hong3, Xinge Yun1

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3871-3888, 2021, DOI:10.32604/cmc.2021.020057 - 24 August 2021

    Abstract The existence of soil macropores is a common phenomenon. Due to the existence of soil macropores, the amount of solute loss carried by water is deeply modified, which affects watershed hydrologic response. In this study, a new improved BP (Back Propagation) neural network method, using Levenberg–Marquand training algorithm, was used to analyze the solute loss on slopes taking into account the soil macropores. The rainfall intensity, duration, the slope, the characteristic scale of macropores and the adsorption coefficient of ions, are used as the variables of network input layer. The network middle layer is used… More >

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