Multiple Regression Models for Lower Heating Value of Municipal Solid Waste in Taiwan

doi:10.1016/j.jenvman.2006.10.025

CNU IR > College of Sustainable Environment and Recreation > Dept. of Tourism Management > Periodical Articles > Item 310902800/22296

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/22296

Title:	Multiple Regression Models for Lower Heating Value of Municipal Solid Waste in Taiwan
Authors:	Y.F. Chang C.J. Lin J.M. Chyan I.M. Chen J.E. Chang
Contributors:	觀光事業管理系環境工程與科學系
Keywords:	Municipal solid waste Physical combustible component Multiple regression analysis Lower heating value
Date:	2007-12
Issue Date:	2010-01-15 14:40:02 (UTC+8)
Abstract:	A multiple regression analysis was used to develop two predictive models of lower heating value (LHV) for municipal solid waste (MSW), using 180 samples gathered from cities and counties in Taiwan during 2001–2002. These models are referred to as the original proposed model (OPM) and the simplified model (SM). The coefficients of multiple determinations for the OPM and SM were 0.983 and 0.975, respectively. To verify the feasibility of the models, a demonstration program based on sampling of MSW in Kaohsiung City was conducted. As a result, the OPM showed superior precision in terms of relative percentage deviation (RPD) and mean absolute percentage error (MAPE), when compared to the conventional models based on the proximate analysis, physical composition and ultimate analysis. The SM was derived by neglecting the three minor physical components used in the OPM. The resulting SM was less precise when compared to the OPM, but it was still acceptable, with a precision level better than the conventional models. It was concluded that the predictability of empirical models could be improved significantly through selection of the appropriate physical components and multiple regression analysis.
Relation:	Journal of Environmental Management 85(4)： p.891-899
Appears in Collections:	[Dept. of Tourism Management] Periodical Articles [Dept. of Environmental Engineering and Science (including master's program)] Periodical Articles

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