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ARTYKUŁ PRZEGLĄDOWY
Prognozowanie powodzi z wykorzystaniem sztucznej Inteligencji (AI): przegląd systematyczny oparty na
metodologii Prisma
1
School of Economics and Commerce, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India, India
2
School of Economics and Commerce, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India, India
Zaznaczeni autorzy mieli równy wkład w przygotowanie tego artykułu
Data nadesłania: 08-08-2025
Data ostatniej rewizji: 05-11-2025
Data akceptacji: 27-11-2025
Data publikacji online: 20-07-2026
Data publikacji: 20-07-2026
Autor do korespondencji
Prasanta Patri
School of Economics and Commerce, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India, 751024, Bhubaneswar, India
School of Economics and Commerce, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India, 751024, Bhubaneswar, India
Economic and Regional Studies 2026;19(2):345-366
SŁOWA KLUCZOWE
KODY KLASYFIKACJI JEL
O33
Q25
C45
DZIEDZINY
STRESZCZENIE
Przedmiot i cel pracy Przedmiot i cel pracy: Celem badania jest zbadanie zastosowania technik sztucznej inteligencji (AI) do prognozowania powodzi. Materiały i metody: Niniejsze badanie systematycznie przegląda 42 artykuły opublikowane w latach 1989–2025. Zbiór danych został wyodrębniony z baz danych Scopus i Web of Science przy użyciu predefiniowanych słów kluczowych i kryteriów włączenia/wykluczenia. Zgodnie z ramami PRISMA-2020 analiza bada techniki AI, metody statystyczne i powszechnie używane słowa kluczowe w prognozowaniu powodzi. Wyniki: Badanie ujawnia, że uczenie maszynowe (ML) i głębokie uczenie (DL) są szeroko stosowanymi technikami AI, z pierwiastkiem średniego błędu kwadratowego (RMSE), który został wykorzystany do prognozowania powodzi. Słowa kluczowe, takie jak „sztuczna inteligencja”, „prognoza”, „prognozowanie powodzi” i „powodzie”, są często używane w tej dziedzinie. Wnioski: Badanie stwierdza, że zaawansowane techniki AI zwiększają dokładność prognozowania, ulepszają systemy wczesnego ostrzegania i promują rozwój opartych na dowodach strategii ograniczania skutków katastrof.
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