AI potential in urban environmental modelling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00640609" target="_blank" >RIV/67985807:_____/25:00640609 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
AI potential in urban environmental modelling
Original language description
ZÁKLADNÍ ÚDAJE: Resilient Society | Application of AI | Climate Change/Energy: Programme and Abstracts. Saxon Academy of Sciences and Humanities in Leipzig and Czech Academy of Sciences, 2025. [Resilient Society | Application of AI | Climate Change/Energy: Second Czech-German Scientific Symposium. 22.09.2025-23.09.2025, Leipzig]. ABSTRAKT: Urban areas are increasingly vulnerable to climate change impacts, particularly heatwaves. Related changes will directly affect the thermal comfort of dwellers. Previous studies revealed interesting patterns, daytime heat stress increases more uniformly across the city, whereas nighttime heat stress exhibits greater spatial heterogeneity. They are driven by factors such as shading, land cover or material properties. However, the influence of the factors above on outdoor thermal comfort, a precise understanding of all effects and interactions or their future prediction, remains insufficiently quantified. The current most accurate models, due to the complexity of urban surroundings, are based on the large-eddy simulation principle. Although this approach enables us to simulate an urban environment in the units of meters, it requires extreme computational cost, this represents a potential for deep learning models designed to predict human thermal comfort in complex urban environments.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10509 - Meteorology and atmospheric sciences
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů