Kristina Mjörnell
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- 2023
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Mark
Estimating the probability distributions of radioactive concrete in the building stock using Bayesian networks
2023) In Expert Systems with Applications(
- Contribution to journal › Article
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Mark
Swedish public and private housing companies’ access to the capital market for financing energy renovation
(
- Contribution to journal › Article
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Mark
Evaluating the Indoor Radon Concentrations in the Swedish Building Stock Using Statistical and Machine Learning
(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Indoor radon interval prediction in the Swedish building stock using machine learning
(
- Contribution to journal › Article
-
Mark
Machine learning models for the prediction of polychlorinated biphenyls and asbestos materials in buildings
(
- Contribution to journal › Article
- 2022
-
Mark
Balancing Social and Economic Sustainability in Renovation with an Affordable Option for Tenants? A Pilot Study from Sweden
(
- Contribution to journal › Article
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Mark
Modeling Artificial Neural Networks to Predict Asbestos-containing Materials in Residential Buildings
2022)(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Predicting the presence of hazardous materials in buildings using machine learning
(
- Contribution to journal › Article
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Mark
Energy efficiency at what cost? Unjust burden-sharing of rent increases in extensive energy retrofitting projects in Sweden
(
- Contribution to journal › Article
- 2021
-
Mark
Approach to manage parameter and choice uncertainty in life cycle optimisation of building design : Case study of optimal insulation thickness
(
- Contribution to journal › Article
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Mark
Renovating on Unequal Premises : A Normative Framework for a Just Renovation Wave in Swedish Multifamily Housing
(
- Contribution to journal › Article
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Mark
The effect of weighting factors on income-related energy inequalities : The case of Sweden’s new building code
(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Machine Learning in Hazardous Building Material Management : Research Status and Applications
(
- Contribution to journal › Article
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Mark
A data-driven approach to assess the risk of encountering hazardous materials in the building stock based on environmental inventories
(
- Contribution to journal › Article
-
Mark
Tracing Hazardous Materials in Registered Records: A Case Study of Demolished and Renovated Buildings in Gothenburg
2021) 2069.(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding