Prediction of significant wave height in the Java Sea using Artificial Neural Network

Illa Rizianiza; Aulia Siti Aisjah

doi:10.1109/ISITIA.2015.7219944

Prediction of significant wave height in the Java Sea using Artificial Neural Network

Illa Rizianiza
, Aulia Siti Aisjah

Institut Teknologi Sepuluh Nopember

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

11 Citations (Scopus)

Abstract

The Java Sea is one of the busiest ship traffic both of domestic and international shipping and potential marine accident is quite high. It is about 43.6% of marine accidents is caused by natural factor. There are two point in this research. Point 1 at latitude 5° 55′29.03″ S longitude 110°51′42.88″ E and point 2 at latitude 4°39′41.99″ S longitude 109°10′7.15″ E. Design predictor of significant wave height is using Artificial Neural Network with backpropagation algorithm. The predictor consists of three inputs. They are significant wave height (m); wind speed (m/s) and wind direction (degree). Architecture of Artificial Neural Network is point 1 [3, 6, 1] dan point 2 [3, 3, 1]. The result RMSE in this prediction are point 1 0.006 m; point 2 0.075 m.

Original language	English
Title of host publication	2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5-9
Number of pages	5
ISBN (Electronic)	9781479977109
DOIs	https://doi.org/10.1109/ISITIA.2015.7219944
Publication status	Published - 24 Aug 2015
Event	16th International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Surabaya, Indonesia Duration: 20 May 2015 → 21 May 2015

Publication series

Name	2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding

Conference

Conference	16th International Seminar on Intelligent Technology and Its Applications, ISITIA 2015
Country/Territory	Indonesia
City	Surabaya
Period	20/05/15 → 21/05/15

UN SDGs

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

SDG 14 Life Below Water

Keywords

backpropagation
significant wave height
wind direction
wind speed

Access to Document

10.1109/ISITIA.2015.7219944

Cite this

Rizianiza, I., & Aisjah, A. S. (2015). Prediction of significant wave height in the Java Sea using Artificial Neural Network. In 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding (pp. 5-9). Article 7219944 (2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISITIA.2015.7219944

Rizianiza, Illa ; Aisjah, Aulia Siti. / Prediction of significant wave height in the Java Sea using Artificial Neural Network. 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 5-9 (2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding).

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title = "Prediction of significant wave height in the Java Sea using Artificial Neural Network",

abstract = "The Java Sea is one of the busiest ship traffic both of domestic and international shipping and potential marine accident is quite high. It is about 43.6\% of marine accidents is caused by natural factor. There are two point in this research. Point 1 at latitude 5° 55′29.03″ S longitude 110°51′42.88″ E and point 2 at latitude 4°39′41.99″ S longitude 109°10′7.15″ E. Design predictor of significant wave height is using Artificial Neural Network with backpropagation algorithm. The predictor consists of three inputs. They are significant wave height (m); wind speed (m/s) and wind direction (degree). Architecture of Artificial Neural Network is point 1 [3, 6, 1] dan point 2 [3, 3, 1]. The result RMSE in this prediction are point 1 0.006 m; point 2 0.075 m.",

keywords = "backpropagation, significant wave height, wind direction, wind speed",

author = "Illa Rizianiza and Aisjah, \{Aulia Siti\}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 16th International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 ; Conference date: 20-05-2015 Through 21-05-2015",

year = "2015",

month = aug,

day = "24",

doi = "10.1109/ISITIA.2015.7219944",

language = "English",

series = "2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

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Rizianiza, I & Aisjah, AS 2015, Prediction of significant wave height in the Java Sea using Artificial Neural Network. in 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding., 7219944, 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding, Institute of Electrical and Electronics Engineers Inc., pp. 5-9, 16th International Seminar on Intelligent Technology and Its Applications, ISITIA 2015, Surabaya, Indonesia, 20/05/15. https://doi.org/10.1109/ISITIA.2015.7219944

Prediction of significant wave height in the Java Sea using Artificial Neural Network. / Rizianiza, Illa; Aisjah, Aulia Siti.
2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2015. p. 5-9 7219944 (2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding).

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

TY - GEN

T1 - Prediction of significant wave height in the Java Sea using Artificial Neural Network

AU - Rizianiza, Illa

AU - Aisjah, Aulia Siti

PY - 2015/8/24

Y1 - 2015/8/24

N2 - The Java Sea is one of the busiest ship traffic both of domestic and international shipping and potential marine accident is quite high. It is about 43.6% of marine accidents is caused by natural factor. There are two point in this research. Point 1 at latitude 5° 55′29.03″ S longitude 110°51′42.88″ E and point 2 at latitude 4°39′41.99″ S longitude 109°10′7.15″ E. Design predictor of significant wave height is using Artificial Neural Network with backpropagation algorithm. The predictor consists of three inputs. They are significant wave height (m); wind speed (m/s) and wind direction (degree). Architecture of Artificial Neural Network is point 1 [3, 6, 1] dan point 2 [3, 3, 1]. The result RMSE in this prediction are point 1 0.006 m; point 2 0.075 m.

AB - The Java Sea is one of the busiest ship traffic both of domestic and international shipping and potential marine accident is quite high. It is about 43.6% of marine accidents is caused by natural factor. There are two point in this research. Point 1 at latitude 5° 55′29.03″ S longitude 110°51′42.88″ E and point 2 at latitude 4°39′41.99″ S longitude 109°10′7.15″ E. Design predictor of significant wave height is using Artificial Neural Network with backpropagation algorithm. The predictor consists of three inputs. They are significant wave height (m); wind speed (m/s) and wind direction (degree). Architecture of Artificial Neural Network is point 1 [3, 6, 1] dan point 2 [3, 3, 1]. The result RMSE in this prediction are point 1 0.006 m; point 2 0.075 m.

KW - backpropagation

KW - significant wave height

KW - wind direction

KW - wind speed

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DO - 10.1109/ISITIA.2015.7219944

M3 - Conference contribution

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T3 - 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding

SP - 5

EP - 9

BT - 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 20 May 2015 through 21 May 2015

ER -

Rizianiza I, Aisjah AS. Prediction of significant wave height in the Java Sea using Artificial Neural Network. In 2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding. Institute of Electrical and Electronics Engineers Inc. 2015. p. 5-9. 7219944. (2015 International Seminar on Intelligent Technology and Its Applications, ISITIA 2015 - Proceeding). doi: 10.1109/ISITIA.2015.7219944

Prediction of significant wave height in the Java Sea using Artificial Neural Network

Abstract

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UN SDGs

Keywords

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