Prediction of hourly indoor Carbon Monoxide concentrations in semiarid regions using Regression and feedforward : backpropagation as a hybrid model
Author
Source
Journal of Palestine Technical College for Research and Studies
Issue
Vol. 2018, Issue 5 (30 Sep. 2018), pp.717-739, 23 p.
Publisher
Palestine Technical College Department of scientific Research
Publication Date
2018-09-30
Country of Publication
Palestine (Gaza Strip)
No. of Pages
23
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Abstract EN
Accurate site-specific forecasting of indoor hourly carbon monoxide (CO) concentrations in school microenvironments is a key issue in air quality research nowadays due to its impact on children‟s health.
This paper investigated the improvement prediction of multiple linear regression (MLR) and feed forward back propagation (FFBP) by combining them with principal component analysis (PCA) for predicting indoor CO concentration in Gaza Strip, Palestine.
Measurements were carried in 12 schools from October 2012 to May 2013 (one academic year).
The results suggested that the selected models are effective forecasting tools and hence can be applicable for short-term forecasting of indoor CO level.
The predicted indoor CO concentration values agree strongly well with the measured data with high coefficients of determination (R2 ) 0.869, 0.870, 0.885 and 0.915 for MLR, PCA-MLR, FFBP and PCA-FFBP, respectively.
Overall, results showed that PCA models combined with MLR and PCA with FFBP improved MLR and FFBP models of predicting indoor CO concentration, with reduced errors by as much as 7.14% (PCA-MLR) and 56.6% (PCA-FFBP).
Moreover, PCA improved the accuracy of the FFBP model by as much as by 3.3%.
American Psychological Association (APA)
al-Bayyumi, Mahir. 2018. Prediction of hourly indoor Carbon Monoxide concentrations in semiarid regions using Regression and feedforward : backpropagation as a hybrid model. Journal of Palestine Technical College for Research and Studies،Vol. 2018, no. 5, pp.717-739.
https://search.emarefa.net/detail/BIM-1169208
Modern Language Association (MLA)
al-Bayyumi, Mahir. Prediction of hourly indoor Carbon Monoxide concentrations in semiarid regions using Regression and feedforward : backpropagation as a hybrid model. Journal of Palestine Technical College for Research and Studies No. 5 (Sep. 2018), pp.717-739.
https://search.emarefa.net/detail/BIM-1169208
American Medical Association (AMA)
al-Bayyumi, Mahir. Prediction of hourly indoor Carbon Monoxide concentrations in semiarid regions using Regression and feedforward : backpropagation as a hybrid model. Journal of Palestine Technical College for Research and Studies. 2018. Vol. 2018, no. 5, pp.717-739.
https://search.emarefa.net/detail/BIM-1169208
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 735-739
Record ID
BIM-1169208