Artificial neural network apply to predict the sea-level change by using satellite data

T. L. Lee; C. J. Huang; C. P. Tsai; C. C. Wen; H. M. Lin

Artificial neural network apply to predict the sea-level change by using satellite data

T. L. Lee, C. J. Huang, C. P. Tsai, C. C. Wen, H. M. Lin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The problem of climate change has become a hot issue around the world, and many countries are raise concern about this critical change. This paper is aim to develop the neural network to evaluate the long term sea-level data and estimate the possible sea level in 2030 based on the five satellite data observed stations at Taiwan. The results indicate that the neural network can be efficiently forecasted sea level change. The average rate of sea level rising around Taiwan in 2030 is 1.8 to 7.4 cm.

Original language	English
Title of host publication	Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan
Publisher	International Society of Offshore and Polar Engineers
Pages	1013-1016
Number of pages	4
ISBN (Print)	9781880653913
Publication status	Published - 2014
Event	24th International Ocean and Polar Engineering Conference, ISOPE 2014 Busan - Busan, Korea, Republic of Duration: 2014 Jun 15 → 2014 Jun 20

Publication series

Name	Proceedings of the International Offshore and Polar Engineering Conference
ISSN (Print)	1098-6189
ISSN (Electronic)	1555-1792

Other

Other	24th International Ocean and Polar Engineering Conference, ISOPE 2014 Busan
Country/Territory	Korea, Republic of
City	Busan
Period	14-06-15 → 14-06-20

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Ocean Engineering
Mechanical Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

Lee, T. L., Huang, C. J., Tsai, C. P., Wen, C. C., & Lin, H. M. (2014). Artificial neural network apply to predict the sea-level change by using satellite data. In Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan (pp. 1013-1016). (Proceedings of the International Offshore and Polar Engineering Conference). International Society of Offshore and Polar Engineers.

Lee, T. L. ; Huang, C. J. ; Tsai, C. P. et al. / Artificial neural network apply to predict the sea-level change by using satellite data. Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan. International Society of Offshore and Polar Engineers, 2014. pp. 1013-1016 (Proceedings of the International Offshore and Polar Engineering Conference).

@inproceedings{c45cceade9c74183be4a4d7e1832b237,

title = "Artificial neural network apply to predict the sea-level change by using satellite data",

abstract = "The problem of climate change has become a hot issue around the world, and many countries are raise concern about this critical change. This paper is aim to develop the neural network to evaluate the long term sea-level data and estimate the possible sea level in 2030 based on the five satellite data observed stations at Taiwan. The results indicate that the neural network can be efficiently forecasted sea level change. The average rate of sea level rising around Taiwan in 2030 is 1.8 to 7.4 cm.",

author = "Lee, {T. L.} and Huang, {C. J.} and Tsai, {C. P.} and Wen, {C. C.} and Lin, {H. M.}",

year = "2014",

language = "English",

isbn = "9781880653913",

series = "Proceedings of the International Offshore and Polar Engineering Conference",

publisher = "International Society of Offshore and Polar Engineers",

pages = "1013--1016",

booktitle = "Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan",

address = "United States",

note = "24th International Ocean and Polar Engineering Conference, ISOPE 2014 Busan ; Conference date: 15-06-2014 Through 20-06-2014",

}

Lee, TL, Huang, CJ, Tsai, CP, Wen, CC & Lin, HM 2014, Artificial neural network apply to predict the sea-level change by using satellite data. in Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan. Proceedings of the International Offshore and Polar Engineering Conference, International Society of Offshore and Polar Engineers, pp. 1013-1016, 24th International Ocean and Polar Engineering Conference, ISOPE 2014 Busan, Busan, Korea, Republic of, 14-06-15.

Artificial neural network apply to predict the sea-level change by using satellite data. / Lee, T. L.; Huang, C. J.; Tsai, C. P. et al.
Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan. International Society of Offshore and Polar Engineers, 2014. p. 1013-1016 (Proceedings of the International Offshore and Polar Engineering Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Artificial neural network apply to predict the sea-level change by using satellite data

AU - Lee, T. L.

AU - Huang, C. J.

AU - Tsai, C. P.

AU - Wen, C. C.

AU - Lin, H. M.

PY - 2014

Y1 - 2014

N2 - The problem of climate change has become a hot issue around the world, and many countries are raise concern about this critical change. This paper is aim to develop the neural network to evaluate the long term sea-level data and estimate the possible sea level in 2030 based on the five satellite data observed stations at Taiwan. The results indicate that the neural network can be efficiently forecasted sea level change. The average rate of sea level rising around Taiwan in 2030 is 1.8 to 7.4 cm.

AB - The problem of climate change has become a hot issue around the world, and many countries are raise concern about this critical change. This paper is aim to develop the neural network to evaluate the long term sea-level data and estimate the possible sea level in 2030 based on the five satellite data observed stations at Taiwan. The results indicate that the neural network can be efficiently forecasted sea level change. The average rate of sea level rising around Taiwan in 2030 is 1.8 to 7.4 cm.

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M3 - Conference contribution

AN - SCOPUS:84906919700

SN - 9781880653913

T3 - Proceedings of the International Offshore and Polar Engineering Conference

SP - 1013

EP - 1016

BT - Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan

PB - International Society of Offshore and Polar Engineers

T2 - 24th International Ocean and Polar Engineering Conference, ISOPE 2014 Busan

Y2 - 15 June 2014 through 20 June 2014

ER -

Lee TL, Huang CJ, Tsai CP, Wen CC, Lin HM. Artificial neural network apply to predict the sea-level change by using satellite data. In Proceedings of the 24th International Ocean and Polar Engineering Conference, ISOPE Busan. International Society of Offshore and Polar Engineers. 2014. p. 1013-1016. (Proceedings of the International Offshore and Polar Engineering Conference).

Artificial neural network apply to predict the sea-level change by using satellite data

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

UN SDGs

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