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On the Use of Ensemble Empirical Mode Decomposition for the Identification of Bridge Frequency from the Responses Measured in a Passing Vehicle

In this paper, ensemble empirical mode decomposition (EEMD) and empirical mode decomposition (EMD) methods are used for the effective identification of bridge natural frequencies from drive-by measurements. A vehicle bridge interaction (VBI) model is crea... see more

vehicle–bridge interaction | bridge identification | empirical mode decomposition | ensemble empirical mode decomposition natural frequency

Infrastructures , 2019

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Ensemble Empirical Mode Decomposition: Image Data Analysis with White-noise Reflection

M. Kopecký

During the last decade, Zhaohua Wu and Norden E. Huang announced a new improvement of the original Empirical Mode Decomposition method (EMD). Ensemble Empirical Mode Decomposition and its abbreviation EEMD represents a major improvement with great versati... see more

Empirical Mode Decomposition (EMD) | Ensemble Empirical Mode Decomposition (EEMD) | image analysis | sifting | Noise-Assigned Data Analysis (NADA)

Acta Polytechnica , 2010

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A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

Bangzhu Zhu

Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble fore... see more

Energies , 2012

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Application of Integrated Artificial Neural Networks Based on Decomposition Methods to Predict Streamflow at Upper Indus Basin, Pakistan

Muhammad Tayyab, Ijaz Ahmad, Na Sun, Jianzhong Zhou and Xiaohua Dong

Consistent streamflow forecasts play a fundamental part in flood risk mitigation. Population increase and water cycle intensification are extending not only globally but also among Pakistan’s water resources. The frequency of floods has increased in... see more

Atmosphere , 2018

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Fault Diagnosis Using Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Power-Based Intrinsic Mode Function Selection Algorithm

Hyungseob Han, Sangjin Cho, Sundeok Kwon and Sang-Bock Cho

In the fault diagnosis system using empirical mode decomposition (EMD), it is important to select the intrinsic mode functions (IMFs) which contain as much fault information as possible and to alleviate the problems of mode mixing and spurious modes. An e... see more

fault diagnosis | improved complete ensemble empirical mode decomposition | intrinsic mode function | neural network

Electronics , 2018

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Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning

Taiyong Li, Zhenda Hu, Yanchi Jia, Jiang Wu and Yingrui Zhou

Crude oil is one of the most important types of energy and its prices have a great impact on the global economy. Therefore, forecasting crude oil prices accurately is an essential task for investors, governments, enterprises and even researchers. However,... see more

crude oil prices | time series forecasting | ensemble empirical mode decomposition (EEMD) | sparse Bayesian learning (SBL) | energy forecasting

Energies , 2018

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An Ensemble Empirical Mode Decomposition, Self-Organizing Map, and Linear Genetic Programming Approach for Forecasting River Streamflow

Jonathan T. Barge, Hatim O. Sharif

This study focused on employing Linear Genetic Programming (LGP), Ensemble Empirical Mode Decomposition (EEMD), and the Self-Organizing Map (SOM) in modeling the rainfall–runoff relationship in a mid-size catchment. Models were assessed with regard to the... see more

Water , 2016

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A New Compound Fault Feature Extraction Method Based on Multipoint Kurtosis and Variational Mode Decomposition

Wenan Cai, Zhaojian Yang, Zhijian Wang and Yiliang Wang

Due to the weak entropy of the vibration signal in the strong noise environment, it is very difficult to extract compound fault features. EMD (Empirical Mode Decomposition), EEMD (Ensemble Empirical Mode Decomposition) and LMD (Local Mean Decomposition) a... see more

multipoint kurtosis | Variational Mode Decomposition | compound fault | feature extraction

Entropy , 2018

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Application of empirical mode decomposition to very low frequency signals for identification of seismic-ionospheric precursor phenomena

Christos Skeberis,Dimitrios T. Xenos,Thomas D. Xenos,Michael E. Contadakis,Dimitrios Arabelos,Georgia Chatzopoulou

This study investigates the application of empirical mode decomposition to signals from very low frequency transmitters in Europe that were received in Thessaloniki, Greece, to provide a method for depicting seismic-ionospheric precursor phenomena that oc... see more

Earthquake Precursor Phenomena | Empirical Mode Decomposition | Hilbert-Huang Transform | Ionospheric disturbances

Annals of Geophysics , 2012

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