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Evaluation of indoor air quality models with the ranked statistical performance measures using available software
Author(s) -
Kadiyala Akhil,
Kumar Ashok
Publication year - 2012
Publication title -
environmental progress and sustainable energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.495
H-Index - 66
eISSN - 1944-7450
pISSN - 1944-7442
DOI - 10.1002/ep.11642
Subject(s) - air quality index , quality (philosophy) , software , computer science , field (mathematics) , set (abstract data type) , statistical model , machine learning , mathematics , geography , philosophy , epistemology , meteorology , programming language , pure mathematics
Over the last two decades, rapid advancements have been made in the field of environmental science and engineering that eventually led to the development of new modeling techniques. It is essential that these newly developed modeling techniques be validated before they are incorporated and applied in the real‐world. Statistical performance measures play a major role in the model validation by comparing the observations with the modeled predictions. One of the serious limitations in the current literature is that very few studies have used a comprehensive set of the ranked performance measures for validating the newly developed indoor air quality models. This study fills the knowledge gap by demonstrating the use of ranked acceptance criteria for validation of an indoor air quality modeling problem in public transit buses using available software. © 2012 American Institute of Chemical Engineers Environ Prog, 2012