Retail sales forecasting presents a significant challenge for large retailers such as Walmart
and Amazon, due to the vast assortment of products, geographical location heterogeneity …

Time-series forecasting is an important task in both academic and industry, which can be
applied to solve many real forecasting problems like stock, water-supply, and sales …

Predicting product sales of large retail companies is a challenging task considering volatile
nature of trends, seasonalities, events as well as unknown factors such as market …

Existing sales forecasting models are not comprehensive and flexible enough to consider
dynamic changes and nonlinearities in sales time-series at the store and product levels. To …

Sales prediction plays a paramount role in the decision-making process for organizations
across various industries. Nonetheless, accurately predicting sales is challenging because …

Retailers must have accurate sales forecasts to efficiently and effectively operate their
businesses and remain competitive in the marketplace. Global forecasting models like …

This article presents a comprehensive study of sales predictions using time series analysis,
focusing on a case study of Walmart sales data. The aim of this study is to evaluate the …

Using time series data to predict future sales changes of products is of great significance to
every retailing company in terms of management and planning of resources. In order to find …

The forecasting of sales forms the foundation of maximizing profits and successful planning
operation at the start of the fiscal year for Business to consumer (B2C) models like Walmart …

The ability to accurately forecast data is highly desirable in a wide variety of fields such as
sales, stocks, sports performance, and natural phenomena. Presented here is a study of …