The sea-level predictions around Taiwan in 2030 using artificial neural network

T. L. Lee; Y. P. Sung; C. J. Huang; C. P. Tsai; C. C. Wen

The sea-level predictions around Taiwan in 2030 using artificial neural network

T. L. Lee, Y. P. Sung, C. J. Huang, C. P. Tsai, C. C. Wen

Department of Hydraulic and Ocean Engineering

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

3 Citations (Scopus)

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 observed stations around 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 4.4 to 9.6 cm.

Original language	English
Title of host publication	Proceedings of the 23rd International Offshore and Polar Engineering Conference, ISOPE 2013
Pages	820-823
Number of pages	4
Publication status	Published - 2013
Event	23rd International Offshore and Polar Engineering Conference, ISOPE 2013 - Anchorage, AK, United States Duration: 2013 Jun 30 → 2013 Jul 5

Publication series

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

Other

Other	23rd International Offshore and Polar Engineering Conference, ISOPE 2013
Country/Territory	United States
City	Anchorage, AK
Period	13-06-30 → 13-07-05

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

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title = "The sea-level predictions around Taiwan in 2030 using artificial neural network",

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 observed stations around 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 4.4 to 9.6 cm.",

author = "Lee, {T. L.} and Sung, {Y. P.} and Huang, {C. J.} and Tsai, {C. P.} and Wen, {C. C.}",

year = "2013",

language = "English",

isbn = "9781880653999",

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

pages = "820--823",

booktitle = "Proceedings of the 23rd International Offshore and Polar Engineering Conference, ISOPE 2013",

note = "23rd International Offshore and Polar Engineering Conference, ISOPE 2013 ; Conference date: 30-06-2013 Through 05-07-2013",

}

Lee, TL, Sung, YP, Huang, CJ, Tsai, CP & Wen, CC 2013, The sea-level predictions around Taiwan in 2030 using artificial neural network. in Proceedings of the 23rd International Offshore and Polar Engineering Conference, ISOPE 2013. Proceedings of the International Offshore and Polar Engineering Conference, pp. 820-823, 23rd International Offshore and Polar Engineering Conference, ISOPE 2013, Anchorage, AK, United States, 13-06-30.

The sea-level predictions around Taiwan in 2030 using artificial neural network. / Lee, T. L.; Sung, Y. P.; Huang, C. J. et al.
Proceedings of the 23rd International Offshore and Polar Engineering Conference, ISOPE 2013. 2013. p. 820-823 (Proceedings of the International Offshore and Polar Engineering Conference).

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

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T1 - The sea-level predictions around Taiwan in 2030 using artificial neural network

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AU - Sung, Y. P.

AU - Huang, C. J.

AU - Tsai, C. P.

AU - Wen, C. C.

PY - 2013

Y1 - 2013

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 observed stations around 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 4.4 to 9.6 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 observed stations around 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 4.4 to 9.6 cm.

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M3 - Conference contribution

AN - SCOPUS:84883700539

SN - 9781880653999

T3 - Proceedings of the International Offshore and Polar Engineering Conference

SP - 820

EP - 823

BT - Proceedings of the 23rd International Offshore and Polar Engineering Conference, ISOPE 2013

T2 - 23rd International Offshore and Polar Engineering Conference, ISOPE 2013

Y2 - 30 June 2013 through 5 July 2013

ER -

The sea-level predictions around Taiwan in 2030 using artificial neural network

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

UN SDGs

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