Back to Search
Start Over
Prediction of household dust mite concentration based on machine learning algorithm
- Source :
- E3S Web of Conferences, Vol 356, p 05057 (2022)
- Publication Year :
- 2022
- Publisher :
- EDP Sciences, 2022.
-
Abstract
- Household dust mites (HDMs) are the important allergens causing allergic diseases in children. A predictive model can help us understand the concentration of HDMs in different areas of China to better prevent and control this kind of allergen. This study used 454 household inspection samples in childrens’ room obtained from China, Children, Homes, Health (CCHH) phase 2 study, conducted during 2013-2014. Spearman correlation and multiple logistic regression were used to explore the influencing factors of HDMs concentrations, by comprehensively considering residents’ lifestyle, building characteristics, environmental exposure, especially dampness-related exposures. This study used the Gradient Boosting Decision Tree(GBDT) algorithm to build the prediction model. The data from CCHH were used to established the prediction model. It was found that there were some differences in the influencing factors between two types of HDMs. The concentration of HDMs were found a significant correlation (p0. 9). This paper provides a reference for predicting the HDMs concentrations in children's bedrooms and the influence of the influencing factors.
- Subjects :
- Environmental sciences
GE1-350
Subjects
Details
- Language :
- English, French
- ISSN :
- 22671242 and 20223560
- Volume :
- 356
- Database :
- Directory of Open Access Journals
- Journal :
- E3S Web of Conferences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.87f699eb88c64dcd9808b17d2145f53a
- Document Type :
- article
- Full Text :
- https://doi.org/10.1051/e3sconf/202235605057