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Received May 11, 2011
Accepted October 26, 2011
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Analysis and prediction of indoor air pollutants in a subway station using a new key variable selection method
JungJin Lim1
YongSu Kim1
TaeSuk Oh1
MinJung Kim1
OnYu Kang1
Jeong Tai Kim2
In-Won Kim3
Jo-Chun Kim4 5
Jae-Sik Jeon6
ChangKyoo Yoo1†
1Department of Environmental Science and Engineering, Center for Environmental Studies, Kyung Hee University, Gyeonggi-do 446-701, Korea 2Department of Architectural Engineering, College of Engineering, Kyung Hee University, Gyeonggi-do 446-701, Korea 3Department of Chemical Engineering, Konkuk University, Seoul 143-701, Korea 4Department of Environmental Engineering, Konkuk University, Seoul 143-701, Korea 5Department of Advanced Technology Fusion, Konkuk University, Seoul 143-701, Korea 6Seoul Metropolitan Government Research Institute of Public Health and Environment, Yongmeori2-gil (Juam-dong1), Gwacheon-si, Gyeonggi-do 427-070, Korea
Korean Journal of Chemical Engineering, August 2012, 29(8), 994-1003(10), 10.1007/s11814-011-0278-z
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Abstract
A new key variable selection and prediction model of IAQ that can select key variables governing indoor air quality (IAQ), such as PM10, CO2, CO, VOCs and formaldehyde, are suggested in this paper. The essential problem of the prediction model is the question of which of the original variables are the most important for predicting IAQ. The next issue is determining the number of key variables that should be ranked. A new index of discriminant importance in the projection (DIP) of Fisher’s linear discriminant (FLD) is suggested for selecting key variables of the prediction models with multiple linear regression (MLR) and partial least squares (PLS), as well as for ranking the importance of input measurement variables on IAQ prediction. The prediction models were applied to a real IAQ dataset from telemonitoring data (TMS) in a metro system. The prediction results of the model using all variables were compared with the results of the model using only key variables of DIP. It shows that the use of our new variable selection method_x000D_
cannot only reduce computational effort, but will also enhance the prediction performances of the models.
Keywords
References
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Kang SN, Hwang HJ, Park YM, Kim HK, Ro CU, Environ.Sci. Technol., 42, 9051 (2008)
Kim M, Rao AS, Yoo C, Ind. Eng. Chem. Res., 48(13), 6363 (2009)
Kim MJ, Kim MH, Kim YS, Yoo CK, Multivariate interpretation on the parameter correlation for over-determined system modeling of ASM model, 10th IWA Conference on Instrumentation Control and Automation (2009)
Kim NJ, Lee SS, Jeon JS, Kim JH, Kim MY, Evaluation of Factors to Affect PM-10 Concentration in Subway Station, Proceedings of Korean Society for Atmospheric Environment, 571 (2006)
Kim YS, Kim JT, Kim IW, Kim JC, Yoo CK, Environ.Eng. Sci., 27, 721 (2010)
Kim YS, Kim MH, Yoo CK, J. Hazard. Mater., 183(1-3), 441 (2010)
Kim Y, Kim M, Lim J, Kim JT, Yoo C, J. Hazard. Mater., 183(1-3), 448 (2010)
King JR, Jackson DA, Environmetrics., 10, 67 (1999)
Kourti T, Anal. Bioanal. Chem., 384, 1043 (2006)
Kwag HK, Jin KW, Kim W, Yang WS, Choi SJ, Park DU, Kor. J. Env. Hlth., 31, 379 (2005)
Liu SS, Liu HL, Yin CS, Wang LS, J. Chem. Inf. Comput.Sci., 43, 964 (2003)
Macgregor JF, Jaeckle C, Kiparissides C, Koutoudi M, AIChE J., 40(5), 826 (1994)
Murruni LG, Solanes V, Debray M, Kreiner AJ, Davidson J, Davidson M, Atoms. Environ., 43, 4577 (2009)
Nieuwenhuijsen MJ, Gomez-Perales JE, Colvile RN, Atmos.Environ., 41, 7995 (2007)
Paivi A, Tarja YT, Anu K, Timo M, Anne H, Kaarle H, Mika RI, Risto H, Tarja K, Matti J, Atmos. Environ., 39, 5059 (2005)
Ramadan Z, Song XH, Hopke PK, Johnson MJ, Scow KM, Anal. Chim. Acta., 446, 233 (2001)
Rigol AM, Camps M, Juan AD, Rauret G, Vidal M, Environ.Sci. Techonol., 42, 4029 (2008)
Yamamoto T, Shimameguri A, Ogawa M, Hashimoto I, Kano V, Application of Statistical Process Monitoring with External Analysis to an Industrial Monomer Plant, IFAC Symposium on Advanced Control of Chemical Processes, 405 (2004)
