A Time Series Sales Data Forecasting Model Based on TCN and Its Three Variants

The forecasting of sales data is a widely studied issue in the fields of artificial intelligence and time series forecasting. TCN (Temporal Convolutional Network) is the most adept at managing time series data among all classical models due to its distinctive architecture. In this paper, we design a TCN-based model for time series forecasting of sales data and propose three variants: a combined model of TCN with RNN, LSTM and GRU to enhance the performance of time series forecasting. Experimental results show that these models perform well in handling the sales data forecasting task, especially the combination of TCN with LSTM performs best in several metrics.