Deep Learning and Statistical Models for Forecasting Transportation Demand: A Case Study of Multiple Distribution Centers

Deep Learning and Statistical Models for Forecasting Transportation Demand: A Case Study of Multiple Distribution Centers

<i>Background</i>: Transportation demand forecasting is an essential activity for logistics operators and carriers. It leverages business operation decisions, infrastructure, management, and resource planning activities. Since 2015, there has been an increase in the use of deep learning...

Full description

Saved in:
Bibliographic Details
Main Authors: Fábio Polola Mamede, Roberto Fray da Silva, Irineu de Brito Junior, Hugo Tsugunobu Yoshida Yoshizaki, Celso Mitsuo Hino, Carlos Eduardo Cugnasca
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Logistics
Subjects:
transportation demand forecasting
supply chain management
LSTM
ARIMA
data preprocessing
Online Access:https://www.mdpi.com/2305-6290/7/4/86
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2305-6290/7/4/86

Similar Items