Explainable Machine Learning for Evapotranspiration Prediction
Document Type
Conference Proceeding
Source of Publication
Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics
Publication Date
1-1-2023
DOI Link
ISBN
978-989-758-670-5
Publisher
SCITEPRESS - Science and Technology Publications
First Page
97
Last Page
104
Disciplines
Computer Sciences
Keywords
Evapotranspiration, Machine Learning, XgBoost, LSTM, Explainable Artificial Intelligence
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Koné, Bamory; Grati, Rima; Bouaziz, Bassem; and Boukadi, Khouloud, "Explainable Machine Learning for Evapotranspiration Prediction" (2023). All Works. 6236.
https://zuscholars.zu.ac.ae/works/6236
Indexed in Scopus
no
Open Access
yes
Open Access Type
Hybrid: This publication is openly available in a subscription-based journal/series
COinS