CNN and LSTM fused neural network-based air PM2.5 concentration prediction method
A PM2.5, concentration prediction technology, applied in biological neural network model, prediction, neural architecture, etc., can solve the problem of inability to extract data deep connections, lack of data analysis, not well suited to changing air pollution conditions, etc. problems, to achieve the effect of achieving environmental management level and high accuracy
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[0040] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.
[0041] The present invention first defines the air pollutant concentration prediction:
[0042] Definition 1 Prediction of air pollutant concentration: mainly through historical pollutants and meteorological information, to predict the concentration of a series of air pollution such as PM2.5 and PM10 in a certain period of time in the future. It is one of the key research topics, so it has certain interdisciplinary nature.
[0043] Definition 2 Traditional forecasting methods: non-deep learning air pollutant concentration forecasting methods are collectively referred to as traditiona...
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