Real-Time Forecasting Model for Monitoring Pollutant with Differential Optical Absorption Spectroscopy
LI Su-wen1,2, LIU Wen-qing2, XIE Pin-hua2, WANG Feng-sui1,YANG Yi-jun1
1. The College of Physics and Electronic Information, Huaibei Coal Industry Teachers College, Huaibei 235000, China 2. Key Laboratory of Environmental Optical & Technology, Anhui Institute of Optics & Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Abstract：For real-time and on-line monitoring DOAS (differential optical absorption spectroscopy) system, a model based on an improved Elman network for monitoring pollutant concentrations was proposed. In order to reduce the systematical complexity, the forecasting factors have been obtained based on the step-wise regression method. The forecasting factors were current concentrations, temperature and relative humidity, and wind speed and wind direction. The dynamic back propagation (BP) algorithm was used for creating training set. The experiment results show that the predicted value follows the real well. So the modified Elman network can meet the demand of DOAS system’s real time forecasting.
Key words：Differential optical absorption spectroscopy;Elman network;Real-time forecasting;Dynamic back propagation algorithm
李素文1,2，刘文清2，谢品华2，王凤随1，杨一军1 . 差分吸收光谱系统监测污染物浓度实时预测模型[J]. 光谱学与光谱分析, 2009, 29(11): 3057-3060.
LI Su-wen1,2, LIU Wen-qing2, XIE Pin-hua2, WANG Feng-sui1,YANG Yi-jun1 . Real-Time Forecasting Model for Monitoring Pollutant with Differential Optical Absorption Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(11): 3057-3060.
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