Is the grey forecasting model suitable for data forecasting with obvious seasonal changes?

1. Grey prediction is a method to predict the system with uncertain factors. Grey prediction is to find the law of system change by identifying the differences of development trends among system factors, that is, to analyze the correlation, generate and process the original data, generate a data sequence with strong regularity, and then establish the corresponding differential equation model, so as to predict the future development trend of things. It uses a series of quantitative values observed at equal intervals to predict the characteristics of the object, constructs a grey prediction model, and predicts the characteristic quantity at a certain moment in the future or the time to reach a certain characteristic quantity.

Second, classification

① Grey time series prediction; That is, using the observed time series reflecting the characteristics of the predicted object, a grey prediction model is constructed to predict the feature quantity at a certain moment in the future or the time to reach a certain feature quantity.

② Distortion prediction; That is, the grey model is used to predict the time when abnormal values appear and the time when abnormal values appear in a specific time period.

③ System prediction; By establishing a set of interrelated grey prediction models for the behavior characteristics of the system, the change of coordination relationship among multiple variables in the system is predicted.

④ Topological prediction; Make the original data into a curve, find all the time points of the fixed value on the curve according to the fixed value, form a time point sequence with the fixed value as the framework, and then establish a model to predict the time points of the fixed value.