SYSTEM FOR PREDICTING DISCHEARGES OVER THE HIGH WATER PERIOD THROUGH THE CLASSIFICATION TECHNIQUES DATA: CASE OF THE GAMBIA RIVER BASIN OF MAKO
DOI:
https://doi.org/10.4314/jfas.v11i2.22Keywords:
data Mining; flow; forecast model; hydrological process; clustering; technicsAbstract
This article examines the trend of flow during the high water period (from July till November) in the basin of Gambia measured at the Mako station of over 2004-2013 period. Methodology consisted at first in calculation and in standardization of data by the method of z-score of some statistical parameters (average, maximum, minimum, range and standard deviation). Obtained series were afterward submitted to classifications techniques such as k-means clustering and Agglomerative Hierarchical Clustering (AHC) of Time Series Data Mining to cluster and discover the discharge patterns in terms of the autoregressive model. From these methods, a forecast model has been developed for the discharge process on average over these years. This study presents basin flow dynamics in high water period from Time Series Data Mining technique.
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