Hybrid deep WaveNet-LSTM architecture for crop yield prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16235-7.pdf
Reference61 articles.
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3. Ang KL-M, Seng JKP (2021) Big data and machine learning with hyperspectral information in agriculture. IEEE Access 9:36699–36718
4. Bhanumathi S, Vineeth M, Rohit N (2019) Crop yield prediction and efficient use of fertilizers. Int Conf Commun Signal Process (ICCSP) 2019:0769–0773. https://doi.org/10.1109/ICCSP.2019.8698087
5. Chen L et al (2021) Estimating soil moisture over winter wheat fields during growing season using machine-learning methods. IEEE J Sel Top Appl Earth Obs Remote Sens 14:3706–3718. https://doi.org/10.1109/JSTARS.2021.3067890
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1. An effective hybrid attention model for crop yield prediction using IoT-based three-phase prediction with an improved sailfish optimizer;Expert Systems with Applications;2024-12
2. Empirical Analysis of Crop Yield Prediction Using Hybrid Model;Signals and Communication Technology;2024
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