Predicting hazardous materials in the Swedish building stock using data mining

Pei-Yu Wu

Research output: Thesis › Licentiate Thesis

481 Downloads (Pure)

Original language	English
Qualification	Licentiate
Awarding Institution	Division of Building Physics
Supervisors/Advisors	Mjörnell, Kristina, Supervisor
Thesis sponsors	Research Institutes of Sweden (RISE) Swedish Foundation for Strategic Research, SSF
Award date	2022 Feb 24
Place of Publication	Lund
Publisher	Lund University
ISBN (Print)	978-91-88722-77-5
ISBN (electronic)	978-91-88722-78-2
Publication status	Published - 2022 Jan 14

Subject classification (UKÄ)

A data-driven approach to assess the risk of encountering hazardous materials in the building stock based on environmental inventories
Wu, P. Y., Mjörnell, K., Mangold, M., Sandels, C. & Johansson, T., 2021 Jul, In: Sustainability (Switzerland). 13, 14, 7836.
Research output: Contribution to journal › Article › peer-review

Open Access
Machine Learning in Hazardous Building Material Management: Research Status and Applications
Wu, P.-Y., Mjörnell, K., Sandels, C. & Mangold, M., 2021 May 11, In: Recent Progress in Materials. 3, 2
Research output: Contribution to journal › Article › peer-review

Open Access

@phdthesis{124d066d5da246faaca2a6c6b126d984,

title = "Predicting hazardous materials in the Swedish building stock using data mining",

author = "Pei-Yu Wu",

year = "2022",

month = jan,

day = "14",

language = "English",

isbn = "978-91-88722-77-5",

series = "TVBH",

publisher = "Lund University",

number = "1028",

type = "Licentiate Thesis",

school = "Division of Building Physics",

}