Predicting building energy consumption in urban neighborhoods using machine learning algorithms

Predicting building energy consumption in urban neighborhoods using machine learning algorithms

Abstract Assessing building energy consumption in urban neighborhoods at the early stages of urban planning assists decision-makers in developing detailed urban renewal plans and sustainable development strategies. At the city-level, the use of physical simulation-based urban building energy modelin...

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Bibliographic Details
Main Authors: Qingrui Jiang, Chenyu Huang, Zhiqiang Wu, Jiawei Yao, Jinyu Wang, Xiaochang Liu, Renlu Qiao
Format: Article
Language:English
Published: Springer 2024-02-01
Series:Frontiers of Urban and Rural Planning
Subjects:
Urban data
Urban building energy modeling (UBEM)
Interpretable machine learning
Ensemble learning
Shanghai central area
Energy consumption
Online Access:https://doi.org/10.1007/s44243-024-00032-3

Internet

https://doi.org/10.1007/s44243-024-00032-3

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