文章基本信息

标题：Feed-Forward Artificial Neural Network Model for Air Pollutant Index Prediction in the Southern Region of Peninsular Malaysia
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作者：Azman Azid ; Hafizan Juahir ; Mohd Talib Latif 等
期刊名称：Journal of Environmental Protection
印刷版ISSN：2152-2197
电子版ISSN：2152-2219
出版年度：2013
卷号：04
期号：12
页码：1-10
DOI：10.4236/jep.2013.412A1001
语种：English
出版社：Scientific Research Publishing
摘要：This paper describes the application of principal component analysis (PCA) and artificial neural network (ANN) to predict the air pollutant index (API) within the seven selected Malaysian air monitoring stations in the southern region of Peninsular Malaysia based on seven years database (2005-2011). Feed-forward ANN was used as a prediction method. The feed-forward ANN analysis demonstrated that the rotated principal component scores (RPCs) were the best input parameters to predict API. From the 4 RPCs, only 10 (CO, O3, PM10, NO2, CH4, NmHC, THC, wind direction, humidity and ambient temp) out of 12 prediction variables were the most significant parameters to predict API. The results proved that the ANN method can be applied successfully as tools for decision making and problem solving for better atmospheric management.
关键词：Air Pollutant Index (API); Principal Component Analysis (PCA); Artificial Neural Network (ANN); Rotated Principal Component Scores (RPCs); Feed-Forward ANN