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Empirical Study on Haze Forecasting Model Based on Neural Network

机译:基于神经网络的雾度预测模型实证研究

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摘要

There are many factors affecting the formation of haze, and the relationship between haze and haze is very complex. The prediction model of BP network with high precision fitting is used to predict the haze based on BP neural network. First, establishing an index system that affects the haze factors. Secondly, the neural network haze prediction model is established. Finally, the BP neural network is used to predict the number of days of the year. The results show that the model has high feasibility and rationality, and has obtained accurate and reliable results, which provides valuable reference for improving the air monitoring of relevant departments.
机译:有许多影响雾度形成的因素,雾度与雾度之间的关系非常复杂。具有高精度配件的BP网络预测模型用于基于BP神经网络的雾度预测。首先,建立影响雾度因子的索引系统。其次,建立了神经网络雾霾预测模型。最后,BP神经网络用于预测一年中的天数。结果表明,该模型具有很高的可行性和合理性,并获得了准确且可靠的结果,为改善相关部门的空气监测提供了有价值的参考。

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