Prediction of Ambient PM10 Concentration with Artificial Neural Network
作者： L. H. Lam , K. M. Mok
DOI: 10.1007/978-3-540-48260-4_122
关键词:
摘要: Previous studies with artificial neural network (ANN) application on air quality prediction show success even most models developed use only temporal data of concentrations; hence mainly time series analyses are performed. It is known that the concentrations pollutants highly related to variations local and regional meteorology conditions which dictate dispersion transport routes them. Many correlation simulating fate impacts released these bases. Meanwhile, ambient may also affect each other therefore making or modelling their behaviours a very complex problem. This study aims at designing economic flexible ANN for 24-hour-ahead predictions respiratory suspended particulates (PM10) taking into account effects from meteorological pollutants.
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