A Fluctuation Correlation Analysis Model for Time Series Data in the Fresh Food Field

Price time series data is a collection of data points precipitated by the price of each product over time, and it is important to analyse the correlation of multiple time series data fluctuations. In order to analyse the correlation of time series fluctuations, the Time Series Fluctuation Correlation Model (TSFCM) is proposed for the complex characteristics of nonlinearity, dynamic changes and multi-dimensional interactions of time series data, which can accurately analyse the correlation, order and direction patterns of two or more time series fluctuations. correlation, sequential and directional patterns of two or more time series fluctuations. The effectiveness of the TSFCM model is verified through comparison experiments with CoFlux algorithm, MFEFC algorithm and DTWFC algorithm. The correlation between different price time series can be analysed, allowing the data to be examined in greater depth to extract latent information. This in turn facilitates the provision of scientific and rational decision support for managers in the fresh food industry. This enhanced decision-making capability will ensure greater accuracy and reliability.