Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

MAHMOODI KUMARS; GHASSEMI HASSAN; Razminia Abolhassan

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF MARINE ENGINEERING Year:2020 | Volume:15 | Issue:30 Page(s): 23-40

Download Full-Text

Persian Verion

View:

374

Download:

Cites:

Information Journal Paper

Title

Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data

Author(s)

MAHMOODI KUMARS | GHASSEMI HASSAN | Razminia Abolhassan | Issue Writer Certificate

Keywords

Extreme Wave Height PredictionQ1

Meteorological DataQ1

ANN ClassifierQ1

Local Outlier FactorQ1

Abstract

Extreme Wave Height Prediction is very challenging due to its very high non-stationarity and non-linearity nature. The main aim of the present study is to propose a new hybrid method based on Local Outlier Factor and Artificial Neural Networks classifier, called LOF-ANN, to accurate prediction of extreme wave height occurrence using historical Meteorological Data. In this study to create models two major hurricanes Dean 2007 and Irene 2011at two locations (NDBC wave buoys stations: http: //www. ndbc. noaa. gov) namely; 41004, 41041 in the Gulf of Mexico, is used. TO detect extreme waves, LOF method is used. The outputs of this method are considered as ANN targets. Extreme and normal waves are considered as Class 0 and class 1, respectively. The inputs of ANN models are historical metrological data, including: Wind direction (WDIR), Wind speed (WSPD), Sea level pressure (PRES), Air temperature (ATMP), and Sea surface temperature (WTMP). To create and evaluation of models, the input data sets are randomly divided into training (80%) and test set (20%). The performance of created models is evaluated using three popular criteria Root Mean Square Error (RMSE) and Receiver Operating Characteristic (ROC) and accuracy parameter. The experiment results show that the proposed method is able to predict the occurrence of extreme wave heights with height accuracy (up to 99%).

Cites

No record.

References

No record.

Cite

APA: Copy

MAHMOODI, KUMARS, GHASSEMI, HASSAN, & Razminia, Abolhassan. (2020). Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data. JOURNAL OF MARINE ENGINEERING, 15(30 ), 23-40. SID. https://sid.ir/paper/60931/en

Vancouver: Copy

MAHMOODI KUMARS, GHASSEMI HASSAN, Razminia Abolhassan. Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data. JOURNAL OF MARINE ENGINEERING[Internet]. 2020;15(30 ):23-40. Available from: https://sid.ir/paper/60931/en

IEEE: Copy

KUMARS MAHMOODI, HASSAN GHASSEMI, and Abolhassan Razminia, “Proposed a New Hybrid LOF-ANN Method to Extreme Wave Height Prediction based on Meteorological Data,” JOURNAL OF MARINE ENGINEERING, vol. 15, no. 30 , pp. 23–40, 2020, [Online]. Available: https://sid.ir/paper/60931/en

Related Journal Papers