Work

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

Year: 2024

Type: article

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.

Source: IET Renewable Power Generation

DOI: 10.1049/rpg2.13122

Authors: Xin‐yun Ye, Yi‐sha Huan, Hui Xu

Institutions: Guangdong University Of Finances and Economics, Guangdong University of Finance, Guangzhou Institute of Science and Technology, Software Engineering Institute of Guangzhou

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $3,500