Exploring statistical and machine learning techniques to identify factors influencing indoor radon concentration-Reference-Cited by-同舟云学术

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Exploring statistical and machine learning techniques to identify factors influencing indoor radon concentration

Published:2023-12 Issue: Volume:905 Page:167024
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Dicu T.,Cucoş A.,Botoş M.,Burghele B.,Florică Ş.,Baciu C.,Ştefan B.,Bălc R.

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference88 articles.

1. Prediction of 222Rn in Danish dwellings using geology and house construction information from central databases;Andersen;Radiat. Prot. Dosim.,2007

2. A statistical evaluation of the geogenic controls on indoor radon concentrations and radon risk;Appleton;J. Environ. Radioact.,2010

3. Short-Term Indoor Radon Gas Assessment in Granitic Public Buildings: A Multi-Parameter Approach;Azevedo,2021

4. Geotectonics of the Metamorphic Terraines from Romania;Balintoni,1997

5. Geological and geochemical factors affecting the radon concentration in homes in Cornwall and Devon, UK;Ball;Environ. Geochem. Health,1993

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Systematic review of statistical methods for the identification of buildings and areas with high radon levels;Frontiers in Public Health;2024-09-11

2. Evaluating radon concentration and temporal correction factors in residential and workplace buildings: A comparison of passive and active methods;Heliyon;2024-09

3. Mapping Indoor Radon Concentrations in Chungcheongbuk-do, South Korea: A Geospatial Analysis using Machine Learning Models;2024-05-02

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