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Reconstructing disrupted water level records in a tide dominated region using data mining technique. Hall. 71-75
The main idea of the M5 model tree machine learning technique is that the algorithm splits the parameter space into subspace and then builds a linear regression model for each subspace. Therefore, the resulting model can be regarded as a modular model. This technique was applied to reconstruct datasets obtained during a measurement campaign in 2008-2009 were split into the training and validation sets. The model was trained using the three hourly water level data from the Delta Apex and Tenggarong measurement station. Water level record show the semi diurnal character of tides in the region, and that the tides are still dominant in the upstream are at the Trenggarong station located about 40 km from the Delta Apex. Four previous time step data
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