Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Domingos, L. (2025). Swarm intelligence for building energy management: An overview of the algorithms used for different types of energy needs. In Leonor Marques Mano Domingos, Maria José Sousa (Ed.), Swarm intelligence application for the cities of the future. (pp. 115-133). Boca Raton: CRC Press.
Exportar Referência (IEEE) 
L. M. Domingos,  "Swarm intelligence for building energy management: An overview of the algorithms used for different types of energy needs", in Swarm intelligence application for the cities of the future, Leonor Marques Mano Domingos, Maria José Sousa, Ed., Boca Raton, CRC Press, 2025, pp. 115-133
Exportar BibTeX 
@incollection{domingos2025_1777606560809,
	author = "Domingos, L.",
	title = "Swarm intelligence for building energy management: An overview of the algorithms used for different types of energy needs",
	chapter = "",
	booktitle = "Swarm intelligence application for the cities of the future",
	year = "2025",
	volume = "",
	series = "",
	edition = "",
	pages = "115-115",
	publisher = "CRC Press",
	address = "Boca Raton",
	url = "https://www.taylorfrancis.com/chapters/edit/10.1201/9781032656786-7/swarm-intelligence-building-energy-management-leonor-domingos?context=ubx&refId=ef182e75-f3cc-4789-ae78-1bfbcc49efca"
}
Exportar RIS 
TY  - CHAP
TI  - Swarm intelligence for building energy management: An overview of the algorithms used for different types of energy needs
T2  - Swarm intelligence application for the cities of the future
AU  - Domingos, L.
PY  - 2025
SP  - 115-133
CY  - Boca Raton
UR  - https://www.taylorfrancis.com/chapters/edit/10.1201/9781032656786-7/swarm-intelligence-building-energy-management-leonor-domingos?context=ubx&refId=ef182e75-f3cc-4789-ae78-1bfbcc49efca
AB  - This chapter presents a bibliometric analysis and a literature review on the application of artificial intelligence (AI) and swarm intelligence (SI) algorithms for building energy management. The analysis underscores the effectiveness of various AI and SI techniques for various buildings’ energy requirements, such as optimizing energy savings, CO2 concentration management, heating and cooling load optimization, HVAC systems, and thermal energy storage. It also explores the potential of these algorithms in Building Information Modeling (BIM). Notable advancements include predictive algorithms for energy consumption, multi-objective optimization for indoor air quality, and hybrid models for heating and cooling efficiency. An analysis regarding the types of algorithms used for each energy requirement is also conducted. The bibliometric analysis validates these findings and identifies new research directions, highlighting well-researched and underexplored topics. This study emphasizes the potential of AI and SI in advancing building energy management while calling for further exploration of SI applications in this field.
ER  -