Prirodne katastrofe i katastrofe izazvane lјudskim delovanjem nezaobilazan su deo postojanja i razvoja lјudske zajednice. Ostvarenje katastrofalnih rizika dovodi do brojnih lјudskih žrtava, uništavanja ekonomske i socijalne infrastrukture i narušavanja životne sredine. Stoga je merenje ovih rizika, u cilјu adekvatnog upravlјanja njima, pretpostavka održivog razvoja. Usled nedovolјnosti informacija o faktorima koji utiču na verovatnoću realizacije katastrofa, kao događaja niskog intenziteta i visoke frekvencije, merenje katastrofalnih rizika predstavlјa svojevrstan izazov u teoriji i praksi. Klasične teorije i metode merenja rizika pokazale su se neadekvatnim u pogledu mogućnosti blagovremenog identifikovanja, pouzdane procene i efikasnog upravlјanja ovim rizicima. Otuda proizilazi potreba za kreiranjem nove naučne paradigme, zasnovane na stohastičkoj teoriji, koja će omogućiti preciznije kvantifikovanje katastrofalnih rizika, pre svega rizika od prirodnih katastrofa. Predmet ovog rada je analiza doprinosa digitalizacije mogućnostima merenja katastrofalnih rizika. Analitika velikih podataka (Big Data), veštačka inteligencija (Artificial Intelligence – AI) i mašinsko učenje (Machine Learning), kao pokretači četvrte industrijske revolucije, donose višestruke mogućnosti u pogledu predviđanja katastrofalnih događaja. Nakon sagledavanja teorijskih i metodoloških pristupa, poseban akcenat u radu će biti stavlјen na potencijale korišćenja ovih tehnologija i relevantnih softverskih rešenja za merenje katastrofalnih rizika.

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