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- W4313307620 abstract "The aim of this work is to predict coastline evolution from satellite images using two methods ARIMA and LSTM. We used a database composed of satellite images of the Akpakpa coastal area taken between September 2015 and October 2021. Positions of the coastline were extracted from each image in the database, using CoastSat. These positions gave us time series that we used to make the predictions. The accuracy of these models was evaluated using four metrics: correlation coefficient R, mean absolute error MAE, mean absolute percentage error MAPE and root mean square error RMSE. For the ARIMA model, the best performances obtained for all the control points are respectively 0.96, 2.20, 6.06 %, 3.28 while the worst are respectively 0.94, 2.65, 12.93 %, 4.05. For the LSTM model, the best performances obtained for all control points are respectively 0.97, 1.41, 4.90%, 2.90 while the worst are respectively 0.93, 2.88, 10.71 %, 3.70. These results indicate that ARIMA and LSTM are both suitable for short-term predictions of coastline evolution in Akpakpa." @default.
- W4313307620 created "2023-01-06" @default.
- W4313307620 creator A5017483838 @default.
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- W4313307620 date "2022-11-16" @default.
- W4313307620 modified "2023-09-27" @default.
- W4313307620 title "Shoreline evolution prediction using satellite images and time series analysis techniques: case of Akpakpa shoreline in Benin Republic" @default.
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- W4313307620 doi "https://doi.org/10.1109/iceccme55909.2022.9988165" @default.
- W4313307620 hasPublicationYear "2022" @default.
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