Application of local climate zones combined with machine learning to predict the impact of urban structure patterns on thermal environment-Reference-Cited by-同舟云学术

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Application of local climate zones combined with machine learning to predict the impact of urban structure patterns on thermal environment

Published:2023-11 Issue: Volume:52 Page:101731
ISSN:2212-0955
Container-title:Urban Climate
language:en
Short-container-title:Urban Climate

Author:

Lau Tsz-Kin,Chen Yu-Cheng,Lin Tzu-Ping

Funder

National Science and Technology Council

Publisher

Elsevier BV

Subject

Atmospheric Science,Urban Studies,Environmental Science (miscellaneous),Geography, Planning and Development

Reference41 articles.

1. LCZ scheme for assessing urban heat island intensity in a complex urban area (Beirut, Lebanon);Badaro-Saliba;Urban Clim.,2021

2. Mapping local climate zones for a worldwide database of the form and function of cities;Bechtel;ISPRS Int. J. Geo Inf.,2015

3. Air temperature characteristics of local climate zones in the Augsburg urban area (Bavaria, southern Germany) under varying synoptic conditions;Beck;Urban Clim.,2018

4. A proof of local convergence for the Adam optimizer;Bock,2019

5. The application of a high-density street-level air temperature observation network (HiSAN): dynamic variation characteristics of urban heat island in Tainan, Taiwan;Chen;Sci. Total Environ.,2018

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1. Urban tree cover provides consistent mitigation of extreme heat in arid but not humid cities;Sustainable Cities and Society;2024-10

2. Climate Change and Food Security Management–based Urban Health Care Systems Using Artificial Intelligence Techniques;Remote Sensing in Earth Systems Sciences;2024-09-04

3. The application of a high-density street-level air temperature observation network (HiSAN): Spatial and temporal variations of thermal and wind condition in different climatic condition types;Sustainable Cities and Society;2024-08

4. Artificial intelligence for predicting urban heat island effect and optimising land use/land cover for mitigation: Prospects and recent advancements;Urban Climate;2024-05

5. Exploring the relationship between air temperature and urban morphology factors using machine learning under local climate zones;Case Studies in Thermal Engineering;2024-03

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