Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network

Abstract The study utilizes the RBF neural network model to evaluate the green development of the Pearl River Delta urban agglomeration, revealing a consistent increase in development levels from 2005 to 2020 despite notable inter‐city variations. The model adeptly handles complex interactions withi...

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Main Authors: Xin‐yun Ye, Yi‐sha Huan, Hui Xu
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Renewable Power Generation
Subjects:
Online Access:https://doi.org/10.1049/rpg2.13122
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author Xin‐yun Ye
Yi‐sha Huan
Hui Xu
author_facet Xin‐yun Ye
Yi‐sha Huan
Hui Xu
author_sort Xin‐yun Ye
collection DOAJ
description Abstract The study utilizes the RBF neural network model to evaluate the green development of the Pearl River Delta urban agglomeration, revealing a consistent increase in development levels from 2005 to 2020 despite notable inter‐city variations. The model adeptly handles complex interactions within urban green development, offering insights into comprehensive impacts and aiding in policy evaluation and optimization. It provides urban planners and decision‐makers with data‐driven support, enhancing the scientific basis and stability of policy‐making.
format Article
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institution Kabale University
issn 1752-1416
1752-1424
language English
publishDate 2024-12-01
publisher Wiley
record_format Article
series IET Renewable Power Generation
spelling doaj-art-b68b43b8fc2d4eecb344ecf721057c532025-01-30T12:15:53ZengWileyIET Renewable Power Generation1752-14161752-14242024-12-0118163659367710.1049/rpg2.13122Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural networkXin‐yun Ye0Yi‐sha Huan1Hui Xu2School of Business AdministrationResearch Institute of Innovation Competitiveness of Guangdong, Hong Kong and Macao Bay Area,Guangdong University of Finance and EconomicsGuangzhou ChinaSchool of Innovation and EntrepreneurshipGuangzhou Institute of Science and TechnologyGuangzhouChinaSchool of Digital Economy and ManagementSoftware Engineering Institute of GuangzhouGuangzhouChinaAbstract The study utilizes the RBF neural network model to evaluate the green development of the Pearl River Delta urban agglomeration, revealing a consistent increase in development levels from 2005 to 2020 despite notable inter‐city variations. The model adeptly handles complex interactions within urban green development, offering insights into comprehensive impacts and aiding in policy evaluation and optimization. It provides urban planners and decision‐makers with data‐driven support, enhancing the scientific basis and stability of policy‐making.https://doi.org/10.1049/rpg2.13122energy consumptionenergy management systems
spellingShingle Xin‐yun Ye
Yi‐sha Huan
Hui Xu
Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network
IET Renewable Power Generation
energy consumption
energy management systems
title Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network
title_full Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network
title_fullStr Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network
title_full_unstemmed Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network
title_short Evaluation of green development of energy consumption in the Pearl River Delta urban agglomeration based on radial basis function neural network
title_sort evaluation of green development of energy consumption in the pearl river delta urban agglomeration based on radial basis function neural network
topic energy consumption
energy management systems
url https://doi.org/10.1049/rpg2.13122
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