Cargando…
A Review of Artificial Neural Network Models Applied to Predict Indoor Air Quality in Schools
Background: Indoor air quality (IAQ) in schools can affect the performance and health of occupants, especially young children. Increased public attention on IAQ during the COVID-19 pandemic and bushfires have boosted the development and application of data-driven models, such as artificial neural ne...
Autores principales: | Dong, Jierui, Goodman, Nigel, Rajagopalan, Priyadarsini |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419013/ https://www.ncbi.nlm.nih.gov/pubmed/37568983 http://dx.doi.org/10.3390/ijerph20156441 |
Ejemplares similares
-
Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings
por: Challoner, Avril, et al.
Publicado: (2015) -
Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)
por: Mad Saad, Shaharil, et al.
Publicado: (2015) -
Indoor air quality and health in schools
por: Ferreira, Ana Maria da Conceição, et al.
Publicado: (2014) -
Applying artificial neural-network model to predict psychiatric symptoms
por: Allahyari, Elahe, et al.
Publicado: (2022) -
Psychosocial Problems, Indoor Air-Related Symptoms, and Perceived Indoor Air Quality among Students in Schools without Indoor Air Problems: A Longitudinal Study
por: Finell, Eerika, et al.
Publicado: (2018)