The application of WUTP-CNN-GRU model in power prediction of desert and floating photovoltaic system
Junxia Jiang, Hongbo Su, Huan Du, Huihui Yin · 2025
Read The application of WUTP-CNN-GRU model in power prediction of desert and floating photovoltaic system by Junxia Jiang, Hongbo Su, Huan Du, Huihui Yin (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12663117.txt.
Description
Junxia Jiang, Hongbo Su, Huan Du, and Huihui Yin build a solar power guess model. Their work from twenty twenty-five serves desert and floating solar plants. Solar power comes and goes, which can shake grid stability.
Data came from a desert plant and a floating plant in China. Weather types were split by a fuzzy cluster method first. A mixed net of CNN and GRU parts then made the guesses. A search method tuned the model values for best fit. Tests beat three other tuned models by a clear margin. The model held up well in sun, cloud, and rain.
Catalog record
| CREATOR | Junxia Jiang, Hongbo Su, Huan Du, Huihui Yin |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |