Olivia Muslim, T. and Ahmed, Ali Najah and Malek, Marlinda Abdul and El-Shafie, Ahmed and El-Shafie, Amr (2019) Investigating the impact of wind on sea level rise using multilayer perceptron neural network (MLP-NN) at coastal area, Sabah. International Journal of Civil Engineering and Technology, 9 (12). pp. 646-656. ISSN 0976-6308,
Full text not available from this repository.Abstract
This study investigating the impact of wind on sea level rise (SLR) using Multilayer Perceptron Neural Network (MLP-NN) at Coastal Area, Sabah. The mean sea level (MSL) and four meteorology parameters namely; wind direction (WD), wind speed (WS), rainfall and mean cloud cover. These meteorological parameter and MSL were monitored regularly each month over a period from January 2007 to December 2016 at three different locations which is Kudat, Kota Kinabalu and Sandakan. Due to small amount of data set, both method the input data were divided into 80 % for training and 20% for testing data respectively.In this study, two scenarios were introduced; the scenario 1 (with wind) WD and WS as input parameter while scenario 2 (without wind)rainfall and mean cloud cover to predict sea level at each stations. Then by using previous monthly sea water level records the model was performed by predicting SLR for1 year, 5 years, 10 years, 30 years, and 50 years ahead in the future. The performance of the models was evaluated according to three statistical indices in terms of the correlation coefficient (R), root mean square error (RMSE) and scatter index (SI). Investigation results indicate that, when compared to measurements, for 50 years prediction, all three models in scenario 2 perform well (with average values of R = 0.6, RMSE = 0.2 cm and SI = 0.4).
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Artificial Neural Network; Artificial Intelligence (AI); Multilayer perceptron Neural Network (MLP NN); Sea Level |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 26 Apr 2019 07:54 |
| Last Modified: | 26 Apr 2019 07:54 |
| URI: | http://eprints.um.edu.my/id/eprint/21082 |
Actions (login required)
 |
View Item |
