A new crude oil price forecasting model based on variational mode decomposition

Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting

(2020) Ganggang Zuo et al.   JOURNAL OF HYDROLOGY

Transductive LSTM for time-series prediction: An application to weather forecasting

(2020) Zahra Karevan et al.   NEURAL NETWORKS

A new financial data forecasting model using genetic algorithm and long short-term memory network

(2020) Yusheng Huang et al.   NEUROCOMPUTING

An optimized VMD method and its applications in bearing fault diagnosis

(2020) Hua Li et al.   MEASUREMENT

A CEEMDAN and XGBOOST-Based Approach to Forecast Crude Oil Prices

(2019) Yingrui Zhou et al.   COMPLEXITY

Multi-step wind power forecast based on VMD-LSTM

(2019) Li Han et al.   IET Renewable Power Generation

Modes decomposition method in fusion with robust random vector functional link network for crude oil price forecasting

(2019) Ranjeeta Bisoi et al.   APPLIED SOFT COMPUTING

A decomposition–integration model with dynamic fuzzy reconstruction for crude oil price prediction and the implications for sustainable development

(2019) Jian Chai et al.   JOURNAL OF CLEANER PRODUCTION

Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network

(2019) Yishun Liu et al.   KNOWLEDGE-BASED SYSTEMS

Predicting the Price of WTI Crude Oil Using ANN and Chaos

(2019) Tao Yin et al.   Sustainability

Effective Long short-term Memory with Differential Evolution Algorithm for Electricity Price Prediction

(2018) Lu Peng et al.   ENERGY

Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM

(2018) Hui Liu et al.   ENERGY CONVERSION AND MANAGEMENT

An adaptive dynamic short-term wind speed forecasting model using secondary decomposition and an improved regularized extreme learning machine

(2018) Na Sun et al.   ENERGY

Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis

(2018) Ranjeeta Bisoi et al.   APPLIED SOFT COMPUTING

A novel visibility graph transformation of time series into weighted networks

(2018) Paiheng Xu et al.   CHAOS SOLITONS & FRACTALS

A review and discussion of decomposition-based hybrid models for wind energy forecasting applications

(2018) Zheng Qian et al.   APPLIED ENERGY

LSTM-EFG for wind power forecasting based on sequential correlation features

(2018) Ruiguo Yu et al.   Future Generation Computer Systems-The International Journal of eScience

Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices

(2017) Salim Lahmiri   IEEE Systems Journal

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

(2017) Jianwei E et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

LSTM: A Search Space Odyssey

(2017) Klaus Greff et al.   IEEE Transactions on Neural Networks and Learning Systems

On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation

(2016) Yamin Wang et al.   ENERGY

Are hybrid models integrated with data preprocessing techniques suitable for monthly streamflow forecasting? Some experiment evidences

(2015) Xiaoli Zhang et al.   JOURNAL OF HYDROLOGY

Variational Mode Decomposition

(2014) Konstantin Dragomiretskiy et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

Crude oil price analysis and forecasting using wavelet decomposed ensemble model

(2012) Kaijian He et al.   ENERGY

Modeling and forecasting crude oil markets using ARCH-type models

(2009) Chin Wen Cheong   ENERGY POLICY