Exploring Forecasting Methods in Supply chain: A comparison of Time Series Analysis and Machine Learning Approaches for Demand Prediction

Abstract

In this study, we use time series analysis and machine learning to forecast demand. The study on demand forecasting is focused on Walmart, a multinational American retailer. to guarantee that the set of inputs utilised to produce the final output are taken from the dataset in order to almost perfectly forecast Walmart's demand. To identify the best accuracy, we will use a number of methods, including the Lasso Regressor, Random Forest Regressor, Gradient Boosting Regressor, Support Vector Regressor, and Time Series Analysis. Iterations were performed to find the best parameters before building the model.