Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology)
The increasing electricity consumption for air cooling and conditioning in buildings has become a significant challenge in Iran, driven by population growth, global warming, limited energy production and distribution capacities, and concerns about the reliance on fossil fuels for electricity generation. This study investigates energy consumption patterns of cooling systems in three buildings at Amirkabir University of Technology: Civil and Environmental Engineering (Building No. 2), Computer Engineering, and Aerospace Engineering. Using energy consumption data, the study identifies key factors related to building characteristics and user behavior that impact cooling energy usage. A Random Forest analysis revealed that among 14 factors, 9 were most significant, with the number of staff, number of students, and the distribution percentage of operating units ranked as the top three. These findings provide insights for developing effective energy conservation strategies tailored to university buildings in similar contexts
Poursedigh, R. , Hatami, F. and Shakeri, E. (2025). Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology). Advances in Energy Sciences and Technologies, 1(1), 66-76. doi: 10.22060/aest.2025.5751
MLA
Poursedigh, R. , , Hatami, F. , and Shakeri, E. . "Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology)", Advances in Energy Sciences and Technologies, 1, 1, 2025, 66-76. doi: 10.22060/aest.2025.5751
HARVARD
Poursedigh, R., Hatami, F., Shakeri, E. (2025). 'Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology)', Advances in Energy Sciences and Technologies, 1(1), pp. 66-76. doi: 10.22060/aest.2025.5751
CHICAGO
R. Poursedigh , F. Hatami and E. Shakeri, "Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology)," Advances in Energy Sciences and Technologies, 1 1 (2025): 66-76, doi: 10.22060/aest.2025.5751
VANCOUVER
Poursedigh, R., Hatami, F., Shakeri, E. Application of random forest algorithm in identification of key factors in building cooling system energy consumption and energy conservation strategies (for office-educational buildings in Amirkabir University of Technology). Advances in Energy Sciences and Technologies, 2025; 1(1): 66-76. doi: 10.22060/aest.2025.5751
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