Prediction of Surface SO2 Concentration in Shanghai Using Artificial Neural Network
2014 ◽
Vol 522-524
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pp. 44-47
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Keyword(s):
Air quality has been deteriorated seriously in Shanghai as a result of urbanization and modernization. A three-layer Artificial Neural Network (ANN) model was developed to forecast the surface SO2 concentration. The subsequent SO2 concentration being the output parameter of this study was estimated by six input parameters such as preceding SO2 concentrations, average daily temperature, sea-level pressure, relative humidity, average daily wind speed and average daily precipitation. Levenberg-Marquarde (LM) backpropagation was tested as the best algorithm and the optimal neuron number for the LM algorithm was found to be eight. ANN testing outputs were proven to be satisfactory with correlation coefficients of about 0.765.
2019 ◽
Vol 6
(8)
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pp. 085107
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2021 ◽
Vol 03
(01)
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pp. 45-52
2018 ◽
2021 ◽
Vol 02
(01)
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