Applying Artificial Neural Networks to Short-Term PM2.5 Forecasting Modeling
作者： Mihaela Oprea , Sanda Florentina Mihalache , Marian Popescu
DOI: 10.1007/978-3-319-44944-9_18
关键词:
摘要: Air pollution with suspended particles from PM2.5 fraction represents an important factor to increasing atmospheric degree in urban areas, a significant potential effect on the health of vulnerable people such as children and elderly. air pollutant concentration continuous monitoring efficient solution for environment management if it is implemented real time forecasting system which can detect trends provide early warning or alerting persons whose might be affected by episodes. The methods PM use mainly statistical artificial intelligence-based models. This paper presents model based protocol, MBP – 2.5 selection best ANN case study two neural network (ANN) models short-term forecasting.
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