Temporal Convolutional Networks and Seasonal Decomposition: AI-Based Predictive Modelling for Retail Sales Volume Forecasting

Authors

  • Cristina Mateos Professor of Human-Computer Interaction, Universidad Politécnica de Madrid (UPM)

Keywords:

temporal convolutional networks, seasonal decomposition, predictive modelling, retail sales volume forecasting, machine learning

Abstract

AI-based forecasting systems have caught the attention of numerous retailers in recent years. An accurate and reliable prediction of sales is an important concern among business professionals because sales predictions are crucial in enhancing the decision-making abilities of any business. AI has a remarkable influence on various areas when integrated into prediction systems. This includes marketing, consumer behavior analysis, and much more.

Downloads

Published

30-06-2026

How to Cite

[1]
“Temporal Convolutional Networks and Seasonal Decomposition: AI-Based Predictive Modelling for Retail Sales Volume Forecasting”, Human-Computer Interaction Persp., vol. 6, no. 1, pp. 25–32, Jun. 2026, Accessed: Jun. 05, 2026. [Online]. Available: https://www.thesciencebrigade.com/hcip/article/view/817