Short-term tidal current prediction based on GA-BP neural network

Tidal current is a novel type of renewable energy for power supply. Accurate and stable tidal current prediction is an important research area in the field of tidal current energy development. In this paper, the GA-BP Neural Network is studied deeply, and the historical time series data and time fac...

Full description

Saved in:
Bibliographic Details
Published inIOP conference series. Earth and environmental science Vol. 513; no. 1; pp. 12061 - 12067
Main Authors Qiao, Xiangshuo, Guo, Fengyi, Zhang, Runfeng
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.06.2020
Subjects
Back propagation networks
Neural networks
Ocean currents
Performance indices
Prediction models
Renewable energy
Tidal currents
Tidal energy
Time factors
Online AccessGet full text

Cover

More Information
Summary:Tidal current is a novel type of renewable energy for power supply. Accurate and stable tidal current prediction is an important research area in the field of tidal current energy development. In this paper, the GA-BP Neural Network is studied deeply, and the historical time series data and time factor are adopted to improve the input. Besides, the prediction model of tidal current components is established based on the experiment data. To validate the effectiveness of the presented method, other five popular prediction models are also introduced and compared. The simulation results show that the model established in this paper is superior to other five models and has better prediction ability in terms of two commonly used performance indices.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/513/1/012061