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A combined architecture of multivariate LSTM with Mahalanobis and Z-Score transformations for oil price forecasting

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Cited by:

  1. Li, Jinchao & Guo, Yuwei, 2025. "A hybrid model based on iTransformer for risk warning of crude oil price fluctuations," Energy, Elsevier, vol. 314(C).
  2. Huang, Haichi & Bian, Chong & Wu, Mengdan & An, Dong & Yang, Shunkun, 2024. "A novel integrated SOC–SOH estimation framework for whole-life-cycle lithium-ion batteries," Energy, Elsevier, vol. 288(C).
  3. Faramarz Saghi & Mustafa Jahangoshai Rezaee, 2023. "Integrating Wavelet Decomposition and Fuzzy Transformation for Improving the Accuracy of Forecasting Crude Oil Price," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 559-591, February.
  4. Li, Qianwen & Qian, Tingyu & Wang, Hui & Sun, Chuanwang, 2025. "Exploring the value of green: The impact factors on China's second-hand green housing prices based on geographically weighted Lasso regressions," Pacific-Basin Finance Journal, Elsevier, vol. 90(C).
  5. Di Zhu & Yinghong Wang & Fenglin Zhang, 2022. "Energy Price Prediction Integrated with Singular Spectrum Analysis and Long Short-Term Memory Network against the Background of Carbon Neutrality," Energies, MDPI, vol. 15(21), pages 1-20, October.
  6. Lei, Yang & Chen, Yuming & Chen, Jinghai & Liu, Xinyan & Wu, Xiaoqin & Chen, Yuqiu, 2023. "A novel modeling strategy for the prediction on the concentration of H2 and CH4 in raw coke oven gas," Energy, Elsevier, vol. 273(C).
  7. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
  8. Max Olinto Moreira & Betania Mafra Kaizer & Takaaki Ohishi & Benedito Donizeti Bonatto & Antonio Carlos Zambroni de Souza & Pedro Paulo Balestrassi, 2022. "Multivariate Strategy Using Artificial Neural Networks for Seasonal Photovoltaic Generation Forecasting," Energies, MDPI, vol. 16(1), pages 1-30, December.
  9. Elżbieta Szaruga & Elżbieta Załoga & Arkadiusz Drewnowski & Sylwia Kowalska & Paulina Dąbrosz-Drewnowska, 2024. "The Role of EU Transport Market Liberalization in Shaping Directions of Rail Energy Consumption Rationalization in Relation to the Export of Goods: The Case of Poland," Energies, MDPI, vol. 17(13), pages 1-33, June.
  10. Zhao, Geya & Xue, Minggao & Cheng, Li, 2023. "A new hybrid model for multi-step WTI futures price forecasting based on self-attention mechanism and spatial–temporal graph neural network," Resources Policy, Elsevier, vol. 85(PB).
  11. Du, Xiaoxu & Tang, Zhenpeng & Chen, Kaijie, 2023. "A novel crude oil futures trading strategy based on volume-price time-frequency decomposition with ensemble deep reinforcement learning," Energy, Elsevier, vol. 285(C).
  12. Li, Ye & Chen, Yiyan & Lean, Hooi Hooi, 2024. "Geopolitical risk and crude oil price predictability: Novel decomposition ensemble approach based ternary interval number series," Resources Policy, Elsevier, vol. 92(C).
  13. Bingchun Liu & Xia Zhang & Yuan Gao & Minghui Xu & Xiaobo Wang, 2025. "China’s Energy Stock Price Index Prediction Based on VECM–BiLSTM Model," Energies, MDPI, vol. 18(5), pages 1-21, March.
  14. Abhibasu Sen & Karabi Dutta Choudhury & Tapan Kumar Datta, 2023. "An analysis of crude oil prices in the last decade (2011-2020): With deep learning approach," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-32, March.
  15. Elżbieta Szaruga & Bartosz Pilecki & Marta Sidorkiewicz, 2023. "The Impact of the COVID-19 Pandemic, Transport Accessibility, and Accommodation Accessibility on the Energy Intensity of Public Tourist Transport," Energies, MDPI, vol. 16(19), pages 1-27, October.
  16. Zhiyong Guo & Fangzheng Wei & Wenkai Qi & Qiaoli Han & Huiyuan Liu & Xiaomei Feng & Minghui Zhang, 2024. "A Time Series Prediction Model for Wind Power Based on the Empirical Mode Decomposition–Convolutional Neural Network–Three-Dimensional Gated Neural Network," Sustainability, MDPI, vol. 16(8), pages 1-20, April.
  17. Faheem Jan & Ismail Shah & Sajid Ali, 2022. "Short-Term Electricity Prices Forecasting Using Functional Time Series Analysis," Energies, MDPI, vol. 15(9), pages 1-15, May.
  18. Gu, Xinyu & See, K.W. & Li, Penghua & Shan, Kangheng & Wang, Yunpeng & Zhao, Liang & Lim, Kai Chin & Zhang, Neng, 2023. "A novel state-of-health estimation for the lithium-ion battery using a convolutional neural network and transformer model," Energy, Elsevier, vol. 262(PB).
  19. Ouyang, Zisheng & Lu, Min & Ouyang, Zhongzhe & Zhou, Xuewei & Wang, Ren, 2024. "A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention," Energy Economics, Elsevier, vol. 138(C).
  20. Lijuan Peng & Zhenglan Xia & Yisu Huang & Zhigang Pan, 2023. "Role of weather in the natural gas market: Insights from the STL‐GARCH‐W method," International Finance, Wiley Blackwell, vol. 26(3), pages 304-323, December.
  21. Liang, Xuedong & Luo, Peng & Li, Xiaoyan & Wang, Xia & Shu, Lingli, 2023. "Crude oil price prediction using deep reinforcement learning," Resources Policy, Elsevier, vol. 81(C).
  22. Jiang, He & Hu, Weiqiang & Xiao, Ling & Dong, Yao, 2022. "A decomposition ensemble based deep learning approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 78(C).
  23. Song Liu & Xinhua Gao & Liu Chen & Sihui Zhou & Yong Peng & Dennis Z. Yu & Xianting Ma & Yan Wang, 2023. "Multi-Traveler Salesman Problem for Unmanned Vehicles: Optimization through Improved Hopfield Neural Network," Sustainability, MDPI, vol. 15(20), pages 1-25, October.
  24. Yu, Yue & Wang, Jianzhou & Jiang, He & Lu, Haiyan, 2025. "How to manage a multifactor-driven crude oil market more effectively? A revisit based on the multiple criteria perspective," Resources Policy, Elsevier, vol. 100(C).
  25. Wu, Chunying & Wang, Jianzhou & Hao, Yan, 2022. "Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm," Resources Policy, Elsevier, vol. 77(C).
  26. Elżbieta Szaruga & Elżbieta Załoga & Arkadiusz Drewnowski & Paulina Dąbrosz-Drewnowska, 2023. "Convergence of Energy Intensity of the Export of Goods by Rail Transport: Linkages with the Spatial Integration and Economic Condition of Countries," Energies, MDPI, vol. 16(9), pages 1-24, April.
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