Improving the simulations of the hydrological model in the karst catchment by integrating the conceptual model with machine learning models

Sezen, Cenk; Sraj, Mojca

doi:10.1016/j.scitotenv.2024.171684

Improving the simulations of the hydrological model in the karst catchment by integrating the conceptual model with machine learning models

THE SCIENCE OF THE TOTAL ENVIRONMENT AN INTERNATIONAL JOURNAL FOR SCIENTIFIC RESEARCH INTO THE ENVIRONMENT AND ITS RELATIONSHIP WITH MAN, sa.926, ss.171684, 2024 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Basım Tarihi: 2024
Doi Numarası: 10.1016/j.scitotenv.2024.171684
Dergi Adı: THE SCIENCE OF THE TOTAL ENVIRONMENT AN INTERNATIONAL JOURNAL FOR SCIENTIFIC RESEARCH INTO THE ENVIRONMENT AND ITS RELATIONSHIP WITH MAN
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Analytical Abstracts, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Communication Abstracts, Compendex, Environment Index, Food Science & Technology Abstracts, Geobase, Greenfile, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
Sayfa Sayıları: ss.171684
Ondokuz Mayıs Üniversitesi Adresli: Evet