Comparison of On-Policy Deep Reinforcement Learning A2C with Off-Policy DQN in Irrigation Optimization: A Case Study at a Site in Portugal

Precision irrigation and optimization of water use have become essential factors in agricul- ture because water is critical for crop growth. The proper management of an irrigation system should enable the farmer to use water efficiently to increase productivity, reduce production costs, and maxi- mi...

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Bibliographic Details
Main Author: Alibabaei, Khadijeh (author)
Other Authors: Gaspar, Pedro D. (author), Assunção, Eduardo (author), Alirezazadeh, Saeid (author), Lima, Tânia M. (author), Soares, Vasco N. G. J. (author), Caldeira, João M. L. P. (author)
Format: article
Language:eng
Published: 2022
Subjects:
agriculture
deep learning
on-policy deep reinforcement learning
irrigation optimization
Online Access:http://hdl.handle.net/10400.11/8001
Country:Portugal
Oai:oai:repositorio.ipcb.pt:10400.11/8001

Internet

http://hdl.handle.net/10400.11/8001

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