Prediction and suggestion of weather in Chengdu based on grey neural network combination model

Yifei Zhang, Yuzhuo Liu, Xiaoming Ye

SouthWest JiaoTong University, Chengdu, China

ABSTRACT

In this paper, a combined model based on grey neural network is proposed to predict the future meteorological data of Chengdu, and the impact of the forecast results on the decision making of agriculture, tourism and energy industry is discussed. First, we use the grey neural network method to predict the future meteorological data by using a small amount of known meteorological data. Second, we build combinatorial models that combine grey neural networks with other forecasting methods to improve forecast accuracy and stability. Finally, we discuss the impact of the forecast results on decision ‐making in agriculture, tourism and energy industries, and make corresponding recommendations. The results show that the combined model based on grey neural network can effectively predict the future meteorological data of Chengdu, and provide a valuable reference for the decision making of related industries.

Keywords: Grey Neural Network; Combinatorial Model; Agriculture; Tourism; Energy

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Yifei Zhang, Yuzhuo Liu, Xiaoming Ye.pdf