Computational intelligence and transient thermal analysis methods for exploratory analysis of source air quality
作者： Gang Sun
关键词: Meteorology 、 Ecological environment 、 Graduate research 、 Air quality index 、 Exploratory analysis 、 Engineering 、 Human health
摘要: It is vital to forecast gas and particle matter concentrations emission rates (GPCER) from livestock production facilities in order assess the impact of airborne pollutants on human health, ecological environment global warming. Modeling source air quality a complex process due abundant nonlinear interactions between GPCER other factors. The objective this study was introduce statistical methods Radial Basis Function (RBF) neural network predict daily Iowa swine deeppit finishing buildings. results show that four variables (outdoor indoor temperature, _____________________________ 1 Reprinted with permission J. Air & Waste Manage. Assoc., 2008, 58(12), 1571-1578. 2 Gang Sun (Ph.D. candidate), Steven Hoff (professor), Brian C. Zelle (research associate) are Department Agricultural Biosystems Engineering at State University. Minda A. Nelson, former graduate research assistant University, currently Burns McDonnell, Inc. (Kansas City, MO). Address Correspondence to: Dr. Hoff, Department, 212 Davidson Hall, Ames, IA 50011; phone: +1-515-294-6180; fax: +1-515-2942255; e-mail: hoffer@iastate.edu.
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