Implementation of the State-of-The-Art Results for Sales Prediction

Tianyi Chen

2024

Abstract

Sales prediction is a projection into the future of expected demand, given a stated set of environmental conditions. It is an integral part of a critical process for matching demand and supply in many companies. Within this text, the topic focuses on the latest domestic and overseas research advances in this domain with prospects and visions for future development. Besides the traditional tools in time series analysis, e.g., the Auto-regressive Integrated Moving Average Model (ARIMA), more Machine Learning (ML) based methods, such as the Long Short-term Memory Network (LSTM) and other Neural Networks (NN), are demonstrating their strong prediction power and are increasingly being applied into hybrid models, which integrate them with the former statistical models. However, with more applications of such ML-based techniques, their lack of explainability is uncovered, causing their low acceptance by decision-makers. Thus, more work is needed to examine the optimization of sales planning with more innovative and customized strategies under the guidance of accurate forecasts. These results serve as an elementary reference to inspire future exploration in this hot spot.

Paper Citation

in Harvard Style

Chen T. (2024). Implementation of the State-of-The-Art Results for Sales Prediction. In Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI; ISBN 978-989-758-726-9, SciTePress, pages 324-330. DOI: 10.5220/0013225000004568

in Bibtex Style

@conference{ecai24,
author={Tianyi Chen},
title={Implementation of the State-of-The-Art Results for Sales Prediction},
booktitle={Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI},
year={2024},
pages={324-330},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013225000004568},
isbn={978-989-758-726-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI
TI - Implementation of the State-of-The-Art Results for Sales Prediction
SN - 978-989-758-726-9
AU - Chen T.
PY - 2024
SP - 324
EP - 330
DO - 10.5220/0013225000004568
PB - SciTePress