期刊
ECOLOGICAL MODELLING
卷 190, 期 1-2, 页码 99-115出版社
ELSEVIER
DOI: 10.1016/j.ecolmodel.2005.01.062
关键词
air-quality management; vehicular pollution; meteorology; traffic characteristic; back-propagation training
类别
Artificial neural networks (ANNs) are useful alternative techniques in modelling the complex vehicular exhaust emission (VEE) dispersion phenomena. This paper describes a step-by-step procedure to model the nitrogen dioxide (NO,) dispersion phenomena using the ANN technique. The ANN-based NO2 models are developed at two air-quality-control regions (AQCRs), one, representing, a traffic intersection (AQCR1) and the other, an arterial road (AQCR2) in the Delhi city. The models are unique in the sense that they are developed for 'heterogeneous(1) traffic conditions and tropical meteorology. The inputs to the model consist of 10 meteorological and 6 traffic characteristic variables. Two-year data, from I January 1997 to 31 December 1998 has been used for model training and data from I January to 31 December 1999, for model testing and evaluation purposes. The results show satisfactory performance of the ANN-based NO2 models on the evaluation data set at both the AQCRs (d = 0.76 for AQCR1, and d = 0.59 for AQCR2). (c) 2005 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据