A systematic study on effective demand prediction using machine learning

Abstract

Effective demand prediction is a crucial aspect of business planning, enabling organizations to optimize their operations and make informed decisions. The advent of big data and machine learning offers new avenues for making precise demand forecasts. This analysis delves into how machine learning algorithms, including regression models, Long Short-Term Memory (LSTM), neural networks, and other advanced techniques, can be employed for this purpose. The discussion will also touch upon the advantages, limitations, and potential future developments in applying machine learning for demand prediction in a business context. Utilizing these methodologies can lead to enhanced decision-making, operational efficiency, and ultimately, a stronger financial performance.

URN:NBN:sciencein.jist.2024.v12.711