Work

Climate-specific machine learning for thermal sensation prediction of buildings in hot desert climates

Year: 2026

Type: article

Source: International Communications in Heat and Mass Transfer

DOI: 10.1016/j.icheatmasstransfer.2026.111175

Authors: Amir Rahmanparast, Muhammed Milani, Bahar Milani, Muhammet Camci, Yakup Karakoyun, Ozgen Acikgoz, Ahmet Selim Dalkilic

Institutions: Yıldız Technical University, Bandırma Onyedi Eylül University, Siirt Üniversitesi, Van Yüzüncü Yıl Üniversitesi, Azerbaijan University of Architecture and Construction

Language: English

Topic: Building Energy and Comfort Optimization

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Climate action, Sustainable cities and communities

Open Access status: closed

Funders: Yildiz Teknik Üniversitesi, Engineering and Physical Sciences Research Council, H2020 Marie Skłodowska-Curie Actions

Awards: G1104789589, Integration of Advanced Experiments, Computation and Data for Innovation in Freeze Casting and Advanced Porous Structures, G919449133

OpenAlex ID: W7148566973

FWCI: 5.098

Cites: 26

Cited by: 2

Related to: 10