2019
DOI: 10.1177/1420326x19852450
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Fast prediction for indoor environment: Models assessment

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Cited by 59 publications
(35 citation statements)
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References 26 publications
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“…& Cao, 2020 ). CFD + MA/AI are effective methods for reducing CFD simulation efforts, and are very popular in indoor environment control ( Feng, Yu, & Cao, 2019 ). With the development of ML/AI, coupling the advanced techniques into outdoor environment design is becoming more and more promising.…”
Section: Discussionmentioning
confidence: 99%
“…& Cao, 2020 ). CFD + MA/AI are effective methods for reducing CFD simulation efforts, and are very popular in indoor environment control ( Feng, Yu, & Cao, 2019 ). With the development of ML/AI, coupling the advanced techniques into outdoor environment design is becoming more and more promising.…”
Section: Discussionmentioning
confidence: 99%
“…), and combine virtual space theory with traditional physical space design methods to form a new urban design method system for use in new situations ( Sanchez-Sepulveda, Fonseca, Franquesa, & Redondo, 2019 ). The integration of big data ( Rahman et al, 2020 ), GIS (Geographic Information System) ( Badach, Voordeckers, Nyka, & Van Acker, 2020 ), dynamic simulation methods for virtual space ( Sanchez-Sepulveda et al, 2019 ; Singh, Kaur, & Kumar, 2020 ) as well as fast prediction models ( Feng, Yu, & Cao, 2019 ; Cao, Yu, & Luo, 2020 ) can be used to build a quantitative group-tool for urban design under the normalization phase of epidemics. Taking satellite cloud map from remote sensing technology and GPS (Global Positioning System) data as input variables, the thematic visualization map of the studied area can be finally output ( Shao, Huq, Cai, Altan, & Li, 2020 ).…”
Section: Reflections On the Reform Of Urban Construction In The Post-mentioning
confidence: 99%
“…The reliability of LVM and LLVM was verified. 32,39,42 Then, the validity of the ANN method based on LLVM was verified through CFD-LLVM simulation, which was used to predict indoor environment variables (i.e. CO 2 concentration) caused by any type of indoor input response.…”
Section: Objectives and Methodsmentioning
confidence: 99%