Results 21 to 30 of about 5,348,114 (153)
Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition [PDF]
Sensors, 2015 A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate ...
Naveed ur Rehman +5 more
doaj +2 more sources
Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition [PDF]
Discrete Dynamics in Nature and Society, 2012 This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition (MEMD) is employed here for multiband representation of multichannel financial time series together. Autoregressive moving average (ARMA)
Md. Rabiul Islam +3 more
doaj +2 more sources
Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm [PDF]
, 2021 Evapotranspiration, as a combination of evaporation and transpiration of water vapour, is a primary component of global hydrological cycles. It accounts for significant loss of soil moisture from the earth to the atmosphere.
Deo, Ravinesh C. +4 more
core +1 more source
A novel method to identify the flow pattern of oil–water two-phase flow
Journal of Petroleum Exploration and Production Technology, 2020 This paper presents a novel method combining extreme learning machine (ELM) and multiple empirical mode decomposition (MEMD) to identify flow patterns of oil–water two-phase flow. The proposed method can recognize accurately five typical flow patterns of
Zhong-Cheng Li, Chun-Ling Fan
doaj +1 more source
A dagging‐based deep learning framework for transmission line flexibility assessment
IET Renewable Power Generation, Volume 17, Issue 5, Page 1092-1105, 6 April 2023., 2023 We have developed a novel dynamic line rating forecasting framework for smart grids and tested the results against real datasets and state‐of‐the‐art machine learning models. Two new DLR forecasting techniques based on MEMD and Dagging are coupled with LSTMs to overcome the limits of single models, address non‐stationary problems, account for catch ...
Azita Morteza +4 more
wiley +1 more source
Energy Science &Engineering, Volume 11, Issue 3, Page 1148-1179, March 2023., 2023 A novel hybrid model is proposed for carbon price forecasting. The effects of exogenous variables on carbon prices are considered at different time scales. Advanced multifactor interpretable models are used for the first time in carbon price forecasting. Analyzing the importance of exogenous variables and the time dependence in carbon price forecasting
Yue Wang +3 more
wiley +1 more source
A Review on the Applications of Time‐Frequency Methods in ECG Analysis
Journal of Healthcare Engineering, Volume 2023, Issue 1, 2023., 2023 The joint time‐frequency analysis method represents a signal in both time and frequency. Thus, it provides more information compared to other one‐dimensional methods. Several researchers recently used time‐frequency methods such as the wavelet transform, short‐time Fourier transform, empirical mode decomposition and reported impressive results in ...
Bikash K. Pradhan +5 more
wiley +1 more source
On the behavior of EMD and MEMD in presence of symmetric alpha-stable noise [PDF]
, 2014 EmpiricalMode Decomposition (EMD) and its extended versions such as Multivariate EMD (MEMD) are data-driven techniques that represent nonlinear and non-stationary data as a sum of a finite zero-mean AM-FM components referred to as Intrinsic Mode ...
NOLAN, John +4 more
core +1 more source
Structural Control and Health Monitoring, Volume 29, Issue 10, October 2022., 2022 Summary Large amounts of data are generated by structural health monitoring systems continuously. Data‐driven methods can transform the available data into valuable information for decision makers. However, these methods for structural health monitoring of bridges are usually developed and tested by analysing a finite element model of the bridge, where
Matteo Vagnoli, Rasa Remenyte‐Prescott
wiley +1 more source
Multiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamics [PDF]
Earth System Dynamics, 2021 Atmosphere and ocean dynamics display many complex features and are characterized by a wide variety of processes and couplings across different timescales.
T. Alberti +3 more
doaj +1 more source