52 citations as recorded by crossref.

1. Background PM10 atmosphere: In the seek of a multifractal characterization using complex networks T. Plocoste et al. https://doi.org/10.1016/j.jaerosci.2021.105777
2. A new high-dimensional time series approach for wind speed, wind direction and air pressure forecasting D. Ambach & W. Schmid https://doi.org/10.1016/j.energy.2017.06.137
3. Multifractal analysis of wind turbine power and rainfall from an operational wind farm – Part 1: Wind turbine power and the associated biases J. Jose et al. https://doi.org/10.5194/npg-31-587-2024
4. Calculation and Analysis of Wind Turbine Health Monitoring Indicators Based on the Relationships with SCADA Data F. Zhang et al. https://doi.org/10.3390/app10010410
5. Spatio-temporal visualization and forecasting of $${\text {PM}}_{10}$$ in the Brazilian state of Minas Gerais K. da Silva et al. https://doi.org/10.1038/s41598-023-30365-w
6. Investigating the time evolution of some parameters describing inflow processes of pedestrians in a room L. Lian et al. https://doi.org/10.1016/j.physa.2018.05.021
7. Data-driven modeling of the wake behind a wind turbine array N. Ali & R. Cal https://doi.org/10.1063/5.0004393
8. ν-Support Vector Regression Model Based on Gauss-Laplace Mixture Noise Characteristic for Wind Speed Prediction S. Zhang et al. https://doi.org/10.3390/e21111056
9. Investigation of Turbulence Behaviour in the Stable Boundary Layer Using Arbitrary-Order Hilbert Spectra W. Wei et al. https://doi.org/10.1007/s10546-016-0227-9
10. Detrended fluctuation analysis of the Ornstein-Uhlenbeck process: Stationarity versus nonstationarity Z. Czechowski & L. Telesca https://doi.org/10.1063/1.4967390
11. Multi-scale/fractal processes in the wake of a wind turbine array boundary layer N. Ali et al. https://doi.org/10.1080/14685248.2019.1590584
12. Fuzzy First-Order Transition-Rules-Trained Hybrid Forecasting System for Short-Term Wind Speed Forecasts Y. Bai et al. https://doi.org/10.3390/en13133332
13. Unsupervised statistical estimation of offshore wind turbine vibration for structural damage detection under varying environmental conditions J. Guo et al. https://doi.org/10.1016/j.engstruct.2022.115005
14. Identifying the scale-dependent motifs in atmospheric surface layer by ordinal pattern analysis Q. Li & Z. Fu https://doi.org/10.1016/j.cnsns.2018.01.002
15. Investigation of local correlations between particulate matter (PM10) and air temperature in the Caribbean basin using Ensemble Empirical Mode Decomposition T. Plocoste et al. https://doi.org/10.1016/j.apr.2020.06.031
16. Scale evolution, intermittency and fluctuation relations in the near-wake of a wind turbine array N. Ali & R. Cal https://doi.org/10.1016/j.chaos.2018.12.018
17. Multi-scale time dependent correlation between synchronous measurements of ground-level ozone and meteorological parameters in the Caribbean Basin T. Plocoste et al. https://doi.org/10.1016/j.atmosenv.2019.05.001
18. Nonlinear dynamics of the sea level time series in the eastern English Channel F. Schmitt et al. https://doi.org/10.1007/s11069-017-3125-7
19. Power fluctuations in turbulence W. Bos & R. Zamansky https://doi.org/10.1103/PhysRevLett.122.124504
20. Scaling and intermittent properties of oceanic and atmospheric pCO2 time series and their difference in a turbulence framework K. Robache et al. https://doi.org/10.5194/npg-32-35-2025
21. Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data A. Gires et al. https://doi.org/10.5194/npg-27-133-2020
22. A Novel Hybrid Strategy Using Three-Phase Feature Extraction and a Weighted Regularized Extreme Learning Machine for Multi-Step Ahead Wind Speed Prediction J. Wang et al. https://doi.org/10.3390/en11020321
23. Role of Deterministic Electromechanical Conversion for Short-Term Fluctuations in Wind Power: A Case Study in Japan F. Raak et al. https://doi.org/10.1103/PhysRevApplied.12.034013
24. Correlated power time series of individual wind turbines: A data driven model approach T. Braun et al. https://doi.org/10.1063/1.5139039
25. Detecting the Causal Nexus between Particulate Matter (PM10) and Rainfall in the Caribbean Area T. Plocoste https://doi.org/10.3390/atmos13020175
26. Exploring the link between multiscale entropy and fractal scaling behavior in near-surface wind M. Nogueira & F. Schmitt https://doi.org/10.1371/journal.pone.0173994
27. Multifractal behavior of an air pollutant time series and the relevance to the predictability Q. Dong et al. https://doi.org/10.1016/j.envpol.2016.11.090
28. Analysis of repulsion states among pedestrians inflowing into a room L. Lian et al. https://doi.org/10.1016/j.physleta.2018.05.055
29. Some statistical properties of aeolian saltation Z. Wang https://doi.org/10.1063/5.0192219
30. Construction of SDE-based wind speed models with exponentially decaying autocorrelation R. Zárate-Miñano & F. Milano https://doi.org/10.1016/j.renene.2016.03.026
31. Fisher–Shannon and detrended fluctuation analysis of MODIS normalized difference vegetation index (NDVI) time series of fire-affected and fire-unaffected pixels X. Li et al. https://doi.org/10.1080/19475705.2017.1337652
32. Turbulence kinetic energy budget and conditional sampling of momentum, scalar, and intermittency fluxes in thermally stratified wind farms N. Ali et al. https://doi.org/10.1080/14685248.2018.1564831
33. Taylor Law in Wind Energy Data R. Calif & F. Schmitt https://doi.org/10.3390/resources4040787
34. The Potential Wind Power Resource in Australia: A New Perspective W. Hallgren et al. https://doi.org/10.1371/journal.pone.0099608
35. DIURNAL VARIATION OF NEAR-SURFACE WIND SPEED: MULTIFRACTAL ANALYSIS T. STOSIC et al. https://doi.org/10.1142/S0218348X25300107
36. Deterministic and Interval Wind Speed Prediction Method in Offshore Wind Farm Considering the Randomness of Wind Q. Chen et al. https://doi.org/10.3390/en13215595
37. The impact of turbulent renewable energy production on power grid stability and quality K. Schmietendorf et al. https://doi.org/10.1140/epjb/e2017-80352-8
38. Multifractal analysis of wind turbine power and rainfall from an operational wind farm – Part 2: Joint analysis of available wind power and rain intensity J. Jose et al. https://doi.org/10.5194/npg-31-603-2024
39. Long-range fluctuations and multifractality in connectivity density time series of a wind speed monitoring network M. Laib et al. https://doi.org/10.1063/1.5022737
40. Modelling Types 1 and 2 Wind Turbines Based on IEC 61400-27-1: Transient Response under Voltage Dips T. García-Sánchez et al. https://doi.org/10.3390/en13164078
41. Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions L. Telesca et al. https://doi.org/10.1016/j.apenergy.2015.10.187
42. Long-range dependence and time-clustering behavior in pedestrian movement patterns in stampedes: The Love Parade case-study L. Lian et al. https://doi.org/10.1016/j.physa.2016.11.048
43. Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines V. Amin Allah & M. Shafiei Mayam https://doi.org/10.1016/j.energy.2017.01.052
44. A Multifractal Random-Walk Description of Atmospheric Turbulence: Small-Scale Multiscaling, Long-Tail Distribution, and Intermittency L. Liu et al. https://doi.org/10.1007/s10546-019-00451-6
45. Multifractal detrended cross-correlation analysis of wind speed and solar radiation T. Plocoste & P. Pavón-Domínguez https://doi.org/10.1063/5.0026354
46. Multiscale analysis of the dynamic relationship between particulate matter (PM10) and meteorological parameters using CEEMDAN: A focus on “Godzilla” African dust event T. Plocoste https://doi.org/10.1016/j.apr.2021.101252
47. Integrated Forecasting Method for Wind Energy Management: A Case Study in China Y. Dong et al. https://doi.org/10.3390/pr8010035
48. Multiscale Analysis of Wind Velocity, Power Output and Rotation of a Windmill O. Medina et al. https://doi.org/10.1016/j.egypro.2015.07.897
49. Discontinuous Jump Behavior of the Energy Conversion in Wind Energy Systems P. Lin et al. https://doi.org/10.1103/PRXEnergy.2.033009
50. Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model W. Bai et al. https://doi.org/10.3390/en10122138
51. Temporal multiscaling characteristics of particulate matter PM10 and ground-level ozone O3 concentrations in Caribbean region T. Plocoste et al. https://doi.org/10.1016/j.atmosenv.2017.08.068
52. A data-driven deep sequence-to-sequence long-short memory method along with a gated recurrent neural network for wind power forecasting T. Ahmad & D. Zhang https://doi.org/10.1016/j.energy.2021.122109