Data for manuscript "Capsule-Based Federated Reinforcement Learning Adaptive Sliding Mode for Anomaly Detection and Control of Floating Wind Turbines"
Year: 2025
Type: dataset
Abstract: This dataset includes simulation outputs, supporting files, parameter tables, and auxiliary code related to the paper: "Capsule-Based Federated Reinforcement Learning Adaptive Sliding Mode for Anomaly Detection and Control of Floating Wind Turbines" with DOI: 10.1371/journal.pone.0336410.The dataset is prepared for reproducing results, plot re-filling, and parametric tests for the floating wind turbine model available in the paper. File Structure- `DataCapsuleFWT.xlsx`- Excel file containing four sheets (one table per sheet) with the following titles:1. "Appendix Table 1: General Properties"2. "Appendix Table 2: Aerodynamic Properties"3. "Appendix Table 3: Mooring Line Properties"4. "Appendix Table 4: Hydrodynamic Properties"- Note: Mathematical symbols (Greek symbols and subscripts) are included as text in the cells
Source: PLoS ONE
Authors: Keighobadi, Jafar, Mohammadian KhalafAnsar, Hadi, Shahhosseini, Mohsen
Institution: University of Tabriz
Language: English
Topic: Wave and Wind Energy Systems
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,382
OpenAlex ID: W7104061676
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