Open AccessKnowledge-Guided Machine Learning (KGML) Platform to Predict Integrated Water Cycle and Associated extremes
Author(s) -
Dipankar Dwivedi,
Grey Nearing,
Hoshin Gupta,
Alden Keefe Sampson,
Laura E. Condon,
Benjamin L. Ruddell,
Daniel Klotz,
Uwe Ehret,
Laura Read,
Praveen Kumar,
Ty P. A. Ferré,
Carl I. Steefel
Publication year - 2021
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/1769733
Subject(s) - water cycle , learning cycle , computer science , gamut , sustainable energy , artificial intelligence , engineering , ecology , mathematics education , mathematics , renewable energy , electrical engineering , biology
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