A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications

A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications

This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable Artificial Intelligence (XAI) models for data imputations and numerical or categorical hydroclimatic predictions from nonlinearly combined multidimensional predictors. The AI models considered in this paper...

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Bibliographic Details
Main Authors: Hakan Başağaoğlu, Debaditya Chakraborty, Cesar Do Lago, Lilianna Gutierrez, Mehmet Arif Şahinli, Marcio Giacomoni, Chad Furl, Ali Mirchi, Daniel Moriasi, Sema Sevinç Şengör
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Water
Subjects:
explainable artificial intelligence
multidimensional data
nonlinearity
explanatory methods
hydroclimatic applications
Online Access:https://www.mdpi.com/2073-4441/14/8/1230

Internet

https://www.mdpi.com/2073-4441/14/8/1230

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