A weekly crude oil price interval-valued prediction architecture on fusion of decomposition technique and adaptive integration

No abstract is available for this paper.

• Publication year

  2025

• Venue

  Energy

• Publication date

  2025-10-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1016/j.energy.2025.137800
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Asymmetric impact of energy prices on financial cycles based on interval time series modeling

  2024cited by this paper
• A novel link prediction model for interval-valued crude oil prices based on complex network and multi-source information

  2024cited by this paper
• Interval prediction of crude oil spot price volatility: An improved hybrid model integrating decomposition strategy, IESN and ARIMA

  2024cited by this paper
• Enhancing interval-valued time series forecasting through bivariate ensemble empirical mode decomposition and optimal prediction

  2024cited by this paper
• A novel crude oil price forecasting model using decomposition and deep learning networks

  2024cited by this paper
• Interval Prediction of Fuel Cell Degradation Based on Voltage Signal Frequency Characteristics with TimesNet-GPR under Dynamic Conditions

  2024cited by this paper
• A new perspective of wind speed forecasting: Multi-objective and model selection-based ensemble interval-valued wind speed forecasting system

  2024cited by this paper
• An ensemble interval prediction model with change point detection and interval perturbation-based adjustment strategy: A case study of air quality

  2023cited by this paper
• Time-Varying Graph Mode Decomposition

  2023cited by this paper
• Oil price forecasting: A hybrid GRU neural network based on decomposition-reconstruction methods

  2023cited by this paper
• A novel interval-based hybrid framework for crude oil price forecasting and trading

  2023cited by this paper
• Optimal combination weight interval-valued carbon price forecasting model based on adaptive decomposition method

  2023cited by this paper
• Improving Value-at-Risk forecast using GA-ARMA-GARCH and AI-KDE models

  2023cited by this paper
• A novel interval dual convolutional neural network method for interval-valued stock price prediction

  2023cited by this paper
• A CNN-BiGRU-AM neural network for AI applications in shale oil production prediction

  2023cited by this paper
• A multi-step ahead point-interval forecasting system for hourly <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e7174" altimg="si4.svg"><mml:msub><mml:mrow><mml:mi mathvariant="normal">PM</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn><mml:mo>.</mml:mo><mml:mn>5</mml:

  2023cited by this paper
• Linear and nonlinear framework for interval-valued PM2.5 concentration forecasting based on multi-factor interval division strategy and bivariate empirical mode decomposition

  2022cited by this paper
• Point and interval forecasting system for crude oil price based on complete ensemble extreme-point symmetric mode decomposition with adaptive noise and intelligent optimization algorithm

  2022cited by this paper
• Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh Evidence Through XGBoost Modeling

  2022cited by this paper
• Exploiting PSO-SVM and sample entropy in BEMD for the prediction of interval-valued time series and its application to daily PM2.5 concentration forecasting

  2022cited by this paper
• Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM

  2022cited by this paper
• Interval prediction approach to crude oil price based on three-way clustering and decomposition ensemble learning

  2022cited by this paper
• A new crude oil price forecasting model based on variational mode decomposition

  2021cited by this paper
• Effective crude oil price forecasting using new text-based and big-data-driven model

  2021cited by this paper
• Forecasting crude oil price with a new hybrid approach and multi-source data

  2021cited by this paper
• Forecasting the U.S. oil markets based on social media information during the COVID-19 pandemic

  2021cited by this paper
• A combined architecture of multivariate LSTM with Mahalanobis and Z-Score transformations for oil price forecasting

  2021cited by this paper
• A combination forecasting model based on hybrid interval multi-scale decomposition: Application to interval-valued carbon price forecasting

  2021cited by this paper
• Bayesian Deep-Learning-Based Health Prognostics Toward Prognostics Uncertainty

  2020cited by this paper
• Multivariate Variational Mode Decomposition

  2019cited by this paper
• Implicit Dimension Identification in User-Generated Text with LSTM Networks

  2019cited by this paper
• A CEEMDAN and XGBOOST-Based Approach to Forecast Crude Oil Prices

  2019cited by this paper
• A novel multi-factor & multi-scale method for PM2.5 concentration forecasting.

  2019cited by this paper
• Point and density forecasts of oil returns: The role of geopolitical risks

  2019cited by this paper
• Interval decomposition ensemble approach for crude oil price forecasting

  2018cited by this paper
• Interval-valued time series forecasting using a novel hybrid HoltI and MSVR model

  2017cited by this paper
• Forecasting of Chinese Primary Energy Consumption in 2021 with GRU Artificial Neural Network

  2017cited by this paper
• Spatio-temporal variation and influence factors of PM2.5 concentrations in China from 1998 to 2014

  2017cited by this paper
• Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting

  2017cited by this paper
• A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting

  2016cited by this paper
• Probabilistic machine learning and artificial intelligence

  2015cited by this paper
• Does China factor matter? An econometric analysis of international crude oil prices

  2014cited by this paper
• Variational Mode Decomposition

  2014cited by this paper
• Multi-output least-squares support vector regression machines

  2013cited by this paper
• Holt’s exponential smoothing and neural network models for forecasting interval-valued time series

  2011cited by this paper
• LIBSVM: A library for support vector machines

  2011cited by this paper
• International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models

  2010cited by this paper
• A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods

  2005cited by this paper
• Modeling and forecasting cointegrated relationships among heavy oil and product prices

  2005cited by this paper
• Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel

  2003cited by this paper
• Multi-dimensional Function Approximation and Regression Estimation

  2002cited by this paper
• Least Squares Support Vector Machine Classifiers

  1999cited by this paper
• Least Squares Support Vector Machines

  year unknowncited by this paper

• Coal mine methane risk prediction method based on data characteristics and decomposition-integration strategy

  2026cites this paper
• Exploring global contagion in artificial Intelligence, supply chain pressure, oil price, and economic policy uncertainty: insights from a bayesian TVP-SV-VAR model

  2025cites this paper