Carbon price prediction based on multi-factor MEEMD-LSTM model [PDF]
Heliyon, 2022 China’s national carbon market has already become the largest carbon market in the world. The prediction of carbon price is extremely important for policymakers and market participants.
Yang Min, Zhu Shuzhen, Li Wuwei
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MEEMD Decomposition–Prediction–Reconstruction Model of Precipitation Time Series [PDF]
Sensors, 2022 To address the problem of low prediction accuracy of precipitation time series data, an improved overall mean empirical modal decomposition–prediction–reconstruction model (MDPRM) is constructed in this paper. First, the non-stationary precipitation time
Yongtao Wang +4 more
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A Hydraulic Pump Fault Diagnosis Method Based on the Modified Ensemble Empirical Mode Decomposition and Wavelet Kernel Extreme Learning Machine Methods [PDF]
Sensors, 2021 To address the problem that the faults in axial piston pumps are complex and difficult to effectively diagnose, an integrated hydraulic pump fault diagnosis method based on the modified ensemble empirical mode decomposition (MEEMD), autoregressive (AR ...
Zhenbao Li +4 more
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Chaotic signal denoising based on energy selection TQWT and adaptive SVD [PDF]
Scientific Reports, 2023 Aiming at the problem of denoising chaotic signals with low signal-to-noise ratio and unknown dynamic system parameters, a new chaotic signal denoising algorithm is proposed, which combines adjustable Q-factor wavelet transform (TQWT) and adaptive ...
Xinlu Yang, Wenbo Wang
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Analysis the self-similarity of network traffic in fractional Fourier transform domain [PDF]
Tongxin xuebao, 2013 Statistical characteristics of network traffic data in FrFT domain were analyzed,which indicates the self-simi-larity feature.Further,Hurst parameter estimation methods based on modified ensemble empirical mode decomposi-tion-detrended fluctuation ...
Tong GUO +3 more
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The Prediction of Gold Futures Prices at the Shanghai Futures Exchange Based on the MEEMD-CS-Elman Model [PDF]
SAGE Open, 2021 The Gold futures market is a complex nonlinear system with the prediction of the futures prices of gold, one of the core issues faced by investors.
Xiaowen Wang, Ying Ma, Wen Li
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A Stochastic source model for the 2015 Mw 7.9 Gorkha, Nepal, Earthquake using Multi-Dimensional Ensemble Empirical Mode Decomposition technique [PDF]
MATEC Web of Conferences, 2018 The present study aims at developing a new strategy to model the spatial variability of slip on the rupture plane using multi-dimensional ensemble empirical mode decomposition (MEEMD) technique. Here, the earthquake slip distribution is split into finite
Sangeetha S, Raghukanth S.T.G
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A Fault Diagnosis Solution of Rolling Bearing Based on MEEMD and QPSO-LSSVM [PDF]
IEEE Access, 2020 The vibration signals of rolling bearing are often non-stationary and non-linear, and consequently it is much more difficult to extract the deep characteristics in the time domain.
Fuzheng Liu, Junwei Gao, Huabo Liu
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Identification of power grids low-frequency oscillations through a combined MEEMD-Prony method [PDF]
Energy ReportsCurrently, the primary focus of power systems is to enhance precision and resilience against interference in identifying low-frequency oscillation modes. This research proposes a new method combined with ensemble empirical mode decomposition (MEEMD) to improve the sensitivity of traditional Prony to noise in parameter analysis of low-frequency ...
Shoaib Ahmed +4 more
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Combined Forecasting Method of Landslide Deformation Based on MEEMD, Approximate Entropy, and WLS-SVM [PDF]
ISPRS International Journal of Geo-Information, 2017 Given the chaotic characteristics of the time series of landslides, a new method based on modified ensemble empirical mode decomposition (MEEMD), approximate entropy and the weighted least square support vector machine (WLS-SVM) was proposed.
Shaofeng Xie +3 more
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