Water level prediction using different numbers of time series data based on chaos approach

Abstract

The prediction of water level in floodplain area is important for early signals and flood control. A total of 6350 hourly water level time series data located at Sungai Dungun were used in this study. The data were divided into training set and testing set. The training set consisted of the first 6000 data which were used to predict the last 350 data. A total of six set data consisting of different amount of training set of data were involved in this study. Consequently, it was used to determine the influence of different amount of data on predicting accuracy by using chaos approach. Those sets of data required a combination of parameters for prediction. In this study, the different amount of data had impacts on the combination of parameter for prediction. In addition, the correlation coefficient showed different values for all sets of data and excellent prediction when they were all used in testing the data. Hence, the different total amount of data will give impact on different combination of parameters and prediction accuracy for water level prediction based on chaos approach in floodplain area.