Research on time series prediction of microclimate in agrivoltaic systems based on the long short-term memory and attention mechanism
The results indicated that the LSTM-Attention model could effectively captured the complex temporal variations in solar radiation and air temperature within AV systems, especially under varying weather conditions. The study provides theoretical support for improving crop management strategies within AV systems.
Authors
- Jiguang Guo
- J.Y. Zhang (ORCID: https://orcid.org/0000-0001-9939-8175)
- Erik H. Murchie (ORCID: https://orcid.org/0000-0002-7465-845X)
- Bingbing Liu
- Encai Bao
- Maohua Xiao
- A. M. Gibbs
- Guijun Xu
- Cuinan Wu
- Chen Yang
Institutions
- Nanjing Agricultural University (CN)
- University of Nottingham (GB)
- Jiangsu Academy of Agricultural Sciences (CN)
- Technology Holding (United States) (US)
- China Power Engineering Consulting Group (China) (CN)
- Ministry of Agriculture (TN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2026-02-03
- DOI
- https://doi.org/10.3389/fpls.2026.1755040
- Primary Topic
- Solar Radiation and Photovoltaics
- Type
- article
- Field-Weighted Citation Impact
- 0.00