Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning

• Main Authors: Gao, Ruobin, Li, Ruilin, Hu, Minghui, Suganthan, Ponnuthurai Nagaratnam, Yuen, Kum Fai
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Electrical and electronic engineering; Time Series Forecasting; Ocean Energy
• Online Access: https://hdl.handle.net/10356/170491
• Institution: Nanyang Technological University

The reliable control of wave energy devices highly relies on the forecasts of wave heights. However, the dynamic characteristics and significant fluctuation of waves’ historical data pose challenges to precise predictions. Neural networks offer a promising solution to forecast the wave heights by ex...