Improving Neural Network Prediction Accuracy for PM₁₀ Individual Air Quality Index Pollution Levels

Abstract

Fugitive dust deriving from construction sites is a serious local source of particulate matter (PM) that leads to air pollution in cities undergoing rapid urbanization in China. In spite of this fact, no study has yet been published relating to prediction of high levels of PM with diameters < 10 lm (PM 10 ) as adjudicated by the Individual Air Quality Index (IAQI) on fugitive dust from nearby construction sites. To combat this problem, the Construction Influence Index (Ci) is introduced in this article to improve forecasting models based on three neural network models (multilayer perceptron, Elman, and support vector machine) in predicting daily PM 10 IAQI one day in advance. To obtain acceptable forecasting accuracy, measured time series data were decomposed into wavelet representations and wavelet coefficients were predicted. Effectiveness of these forecasters were tested using a time series recorded between January 1, 2005, and December 31, 2011, at six monitoring stations situated within the urban area of the city of Wuhan, China. Experimental trials showed that the improved models provided low root mean square error values and mean absolute error values in comparison to the original models. In addition, these improved models resulted in higher values of coefficients of determination and AHPC (the accuracy rate of high PM 10 IAQI caused by nearby construction activity) compared to the original models when predicting high PM 10 IAQI levels attributable to fugitive dust from nearby construction sites.

Particulate Matter Sampling Techniques and Data Modelling Methods

“…The time series data were decomposed into wavelet functions, and wavelet coeicients were predicted. All three models were found to give similar results, and when CI was included, the model gave improved predictions for peaks in PM 10 concentration [54].…”

Impact of Open Burning Refuse on Air Quality: In the Case of “Hidar Sitaten” at Addis Ababa, Ethiopia

“… 45 Study conducted in China showed that fugitive dust deriving from construction sites is a serious local source of PM 2.5 that leads to air pollution in cities undergoing rapid urbanization. 46 Moreover, study conducted in Nepal shown that overall average PM 2.5 concentrations and peak 1 hour CO concentrations exceeded WHO Indoor Air Quality Guidelines. 47 …”

Hava Kali̇te İndeksi̇ İle Meteoroloji̇k Parametreler Arasindaki̇ İli̇şki̇ni̇n Çoklu Regresyon Yöntemi̇ İle Beli̇rlenmesi̇

“…Hava kalitesi indeksi (HKİ), hava kirliliğine bağlı sağlık riski düzeyini ifade etmek için kullanılan bir terim olup, hava kalitesini basit ve anlaşılabilir bir şekilde açıklamaktadır [22,24]. HKİ, insan sağlığına ilişkin olarak farklı bileşenlerin hava kalitesi hakkında düzgün bir şekilde rapor vermek için kullanılan kantitatif bir ölçüdür [23]. HKİ değeri, bir bölgedeki her bir kirletici için ayrı ayrı hesaplanır ve her bir kirletici için hesaplanan en yüksek HKİ, o güne ait HKİ değerini oluşturmaktadır [24].…”