Using probabilistic sampling-based sensitivity analyses for indoor air quality modelling

Building and Environment

Volumn 78, Issue , 2014, Pages 171-182

  Das, Payel ^a   Shrubsole, Clive ^a   Jones, Benjamin ^b   Hamilton, Ian ^a   Chalabi, Zaid ^c   Davies, Michael ^a   Mavrogianni, Anna ^a   Taylor, Jonathon ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^c LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

Housing stock; Indoor air quality; Metamodel; Probabilistic sampling; Sensitivity analysis

Indexed keywords

HOUSING; INDOOR AIR POLLUTION; NEURAL NETWORKS; REGRESSION ANALYSIS;

CORRELATION COEFFICIENT; HOUSING STOCK; INDOOR AIR QUALITY; LATIN HYPERCUBE SAMPLING METHODS; LINEAR REGRESSION METHODS; META MODEL; PROBABILISTIC FRAMEWORK; PROBABILISTIC SAMPLING;

SENSITIVITY ANALYSIS;

AIR QUALITY; ARTIFICIAL NEURAL NETWORK; HOUSING; INDOOR AIR; MODELING; PROBABILITY; SENSITIVITY ANALYSIS;

ENGLAND; UNITED KINGDOM;

EID: 84901003154     PISSN: 03601323     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.buildenv.2014.04.017     Document Type: Article

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