{"refrec":{"BRefID":361026,"RR":"<b>Nossent, J.</b> (2023). Exploreren van de mogelijkheden voor Big Data en Data-mining toepassingen: eindrapport. Versie 1.0. <i>WL Rapporten</i>, 17_070_1. Waterbouwkundig Laboratorium: Antwerpen. VII, 17 pp. <a href=\"https://dx.doi.org/10.48607/152\" target=\"_blank\">https://dx.doi.org/10.48607/152</a>","BEntID":358741,"PublicFlag":1,"CheckedFlag":0,"wosflag":0,"vabbflag":0,"RefStringPartII":". Versie 1.0. <i>WL Rapporten</i>, 17_070_1. Waterbouwkundig Laboratorium: Antwerpen.  VII, 17 pp. <a href=\"https://dx.doi.org/10.48607/152\" target=\"_blank\">https://dx.doi.org/10.48607/152</a>","DocTypID":13,"DocType":"Reports","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Nossent, J.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Nossent, J.","Englishabstract":null,"AbstractOtherLang":"In het kader van de doelstelling uit het departementale ondernemingsplan van 2017, werden de afgelopen  jaren de mogelijkheden voor het gebruik van Big Data en Data-mining technieken, en meer bepaald Machine  Learning technieken, voor het Waterbouwkundig Laboratorium geëxploreerd. Deze innovatieve technieken  vinden immers meer en meer ingang in ons vakgebied en gezien de grote hoeveelheid beschikbare data bij  het WL, zou dit dus op termijn een sterke meerwaarde kunnen betekenen.<br>Voor het exploreren van de mogelijkheden hiervoor en voor de nodige kennisopbouw, werd er enerzijds  samengewerkt met enkele universitaire groepen – waarbij studenten aan de slag gingen onder leiding van  een expert in het vakgebied – en werd ook een case uitgewerkt in samenwerking met het MOW datalab. De  resultaten van deze verschillende projecten worden samengevat in dit rapport. Naast enkele veelbelovende  resultaten, werden ook nog een aantal hiaten en moeilijkheden geïdentificeerd. Het is dan ook duidelijk dat  dit rapport geen eindpunt kan en mag zijn voor het gebruik van deze technieken, aangezien de mogelijkheden  zeer groot zijn en er nog veel progressie mogelijk is. 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