<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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%.</p></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%.

A Simulation Model of Seawater Vertical Temperature by Using Back-Propagation Neural Network

College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China

Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga 8168580, Japan

Collaborative Innovation Center for Distant-water Fisheries, Shanghai Ocean University, Shanghai 201306, China

Polish Maritime Research

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

This study proposed a neural-network-based model to estimate the ocean vertical water temperature from the surface temperature in the northwest Pacific Ocean....

A Simulation Model of Seawater Vertical Temperature by Using Back-Propagation Neural Network

Publié en ligne: 15 oct. 2015

Pages: 82 - 88

DOI: https://doi.org/10.1515/pomr-2015-0037

Mots clés
neural network, Agro data, vertical structure, surface temperature

© 2015

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

A Simulation Model of Seawater Vertical Temperature by Using Back-Propagation Neural Network

Publié en ligne: 15 oct. 2015

Pages: 82 - 88

DOI: https://doi.org/10.1515/pomr-2015-0037

Mots clésneural network, Agro data, vertical structure, surface temperature

© 2015

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

Mots clés
neural network, Agro data, vertical structure, surface temperature