Intermittent demand forecasting with transformer neural networks

Gaomin Zhang; Yusen Xia; Maohua Xie

doi:10.1007/s10479-023-05447-7

ScienceGate Book Chapters

JOURNAL ARTICLE

Intermittent demand forecasting with transformer neural networks

Gaomin Zhang Yusen Xia Maohua Xie

Year: 2023 Journal: Annals of Operations Research Vol: 339 (1-2)Pages: 1051-1072 Publisher: Springer Science+Business Media

DOI: 10.1007/s10479-023-05447-7

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Transformer Artificial neural network Spare part Artificial intelligence Machine learning Long short term memory Theory of computation Deep learning Recurrent neural network Demand forecasting Reinforcement learning Feed forward Operations research Engineering Operations management

Metrics

Cited By

4.21

FWCI (Field Weighted Citation Impact)

Refs

0.93

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Forecasting Techniques and Applications

Social Sciences → Decision Sciences → Management Science and Operations Research

Energy Load and Power Forecasting

Physical Sciences → Engineering → Electrical and Electronic Engineering

Stock Market Forecasting Methods

Social Sciences → Decision Sciences → Management Science and Operations Research

Intermittent demand forecasting with transformer neural networks

Metrics

Citation History

Topics

Related Documents

Single-hidden layer neural networks for forecasting intermittent demand

Intermittent demand forecasts with neural networks

Intermittent Time Series Demand Forecasting Using Dual Convolutional Neural Networks

Neural Network with Specialized Knowledge for Forecasting Intermittent Demand

Forecasting with Recurrent Neural Network in Intermittent Demand Data