Empirical Mode Decomposition and Fourier analysis of Caspian Sea level's time series

Dehghan, Yaser; Sadrinasab, Masoud; Chegini, Vahid

doi:10.1016/j.oceaneng.2022.111114

Cited by 7 publications

(1 citation statement)

References 34 publications

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“…Winds are usually mild and unpredictable throughout the southwest and inter-monsoon seasons [7]. The low wind speed zone is expected to include 70% of the globe, which includes India [8,9]. With the right approach and dependable wind technology, it is thought that power can be produced even in regions with low wind speeds [10].…”

Section: Introductionmentioning

confidence: 99%

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

M K,

et al. 2024

E3S Web of Conf.

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To determine the wind energy potential, the probability density function is typically used. For data distribution with modest wind speeds, this paper developed a three-parameter Weibull model. The distribution factors were determined using the maximal likelihood technique. The world renowned, user-friendly programming language Matrix Laboratory (MATLAB) processes all data that needs analysis. A comparison was made between the 3-factor Weibull, the 2-factor Weibull, and Rayleigh through R2 and root mean square error (RMSE). The ECMWF Reanalysis v5 (ERA 5) reanalysis's hourly wind speeds are statistically represented by these three distributions. Due to its placement between the optimal R2 and RMSE, the three-parameter Weibull model achieves good results. Weibull with three parameters has a R2 of 0.9898, Weibull with two parameters has a R2 of 0.9886, and Rayleigh has a R2 of 0.5162. The root-mean-squared errors (RMSEs) for Rayleigh, 2-factor and 3-factor Weibull, are 0.0082 and 0.0070, respectively.

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Section: Introductionmentioning

confidence: 99%

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

M K,

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

show abstract

Geographic heterogeneity of activation functions in urban real-time flood forecasting: Based on seasonal trend decomposition using Loess-Temporal Convolutional Network-Gated Recurrent Unit model

Huan

2024

Journal of Hydrology

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Analysis of sea level fluctuations around the Australian coast with anomaly time series analysis approach

Dehghan

Zenooz

Pour

2022

Marine Environmental Research

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Empirical Mode Decomposition and Fourier analysis of Caspian Sea level's time series

Cited by 7 publications

References 34 publications

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

Geographic heterogeneity of activation functions in urban real-time flood forecasting: Based on seasonal trend decomposition using Loess-Temporal Convolutional Network-Gated Recurrent Unit model

Analysis of sea level fluctuations around the Australian coast with anomaly time series analysis approach

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