Journals - MOST Wiedzy

Your account

Login
Polish Maritime Research Logo
Polish Maritime Research

A SIMULATION MODEL OF SEAWATER VERTICAL TEMPERATURE BY USING BACK-PROPAGATION NEURAL NETWORK

Abstract

This study proposed a neural-network-based model to estimate the ocean vertical water temperature from the surface temperature in the northwest Pacific Ocean. The performance of the model and the sources of errors were assessed using the Gridded Argo dataset including 576 stations with 26 vertical levels from surface (0 m)–2,000 m over the period of 2007–2009. The parameter selection, model building, stability of the neural network were also investigated. According to the results, the averaged root mean square error (RMSE) of estimated temperature was 0.7378°C and the correlation coefficient R was 0.9967. More than 67% of the estimates from the four selected months (January, April, July and October) lay within ± 0.5 °C. When counting with errors lower than ± 1°C, the lowest percentage was 83%.

Keywords:

neural network, Agro data, vertical structure, surface temperature

Details

Issue
Vol. 22 No. S1(86) (2015)
Section
Latest Articles
Published
15-10-2015
DOI:
https://doi.org/10.1515/pomr-2015-0037
Licencja:
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Open Access License

This journal provides immediate open access to its content under the Creative Commons BY 4.0 license. Authors who publish with this journal retain all copyrights and agree to the terms of the CC BY 4.0 license.

 

Authors

  • Ning Zhao

    Shanghai Ocean University, College of Marine Sciences; Kyushu University, Interdisciplinary Graduate School of Engineering Sciences
  • Zhen Han

    Shanghai Ocean University, College of Marine Sciences, Collaborative Innovation Center for Distant-water Fisheries

Download paper

Most read articles by the same author(s)