SYSTEM FOR PREDICTING DISCHEARGES OVER THE HIGH WATER PERIOD THROUGH THECLASSIFICATION TECHNIQUES DATA: CASE OF THE GAMBIA RIVER BASIN OF MAKO

dc.contributor.authorFaye, C
dc.date.accessioned2023-05-29T10:14:34Z
dc.date.available2023-05-29T10:14:34Z
dc.date.issued2019-05-01
dc.descriptionarticleen_US
dc.description.abstractThis article examines the trend of flow during the high water period(from July till November) in the basin of Gambiameasured at the Mako station of over 2004-2013 period. Methodology consisted at first in calculation and in standardizationof 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 modelhas been developed for the discharge process on average over these years. This study presents basin flow dynamics in high water periodfrom Time Series Data Mining techniqueen_US
dc.identifier.citationC. Faye, SYSTEM FOR PREDICTING DISCHEARGES OVER THE HIGH WATER PERIOD THROUGH THECLASSIFICATION TECHNIQUES DATA: CASE OF THE GAMBIA RIVER BASIN OF MAKO. Journal of Fundamental and sciences. vol.11, no 2. May 2019. Faculty of exact sciences. university of el oued. [visited in 01/05/2019]. available from [[email protected]]en_US
dc.identifier.urihttps://dspace.univ-eloued.dz/handle/123456789/24743
dc.language.isoenen_US
dc.publisheruniversity of eloued -جامعة الواديen_US
dc.relation.ispartofseries1112-9867;
dc.subjectdata Mining, flow, forecast model, hydrological process, clustering; technicsen_US
dc.titleSYSTEM FOR PREDICTING DISCHEARGES OVER THE HIGH WATER PERIOD THROUGH THECLASSIFICATION TECHNIQUES DATA: CASE OF THE GAMBIA RIVER BASIN OF MAKOen_US
dc.typeArticleen_US

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