Ship order book forecasting by an ensemble deep parsimonious random vector functional link network

• Main Authors: Cheng, Ruke, Gao, Ruobin, Yuen, Kum Fai
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Forecasting; Shipping market
• Online Access: https://hdl.handle.net/10356/175804
• Institution: Nanyang Technological University

Efficient forecasting of ship order books holds immense significance in the maritime industry, enabling companies to optimize their operations, allocate resources effectively, and make informed decisions. However, volatile characteristics within historical order books pose challenges in achieving re...