| dc.description.abstract | 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.
Keywords: data Mining, flow, forecast model, hydrological process, clustering; technics | en_US |
