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Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products. (2023). Zhang, Yun ; Xu, Xiaojie.
In: Mineral Economics.
RePEc:spr:minecn:v:36:y:2023:i:4:d:10.1007_s13563-022-00357-9.

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  1. Forecasts of coking coal futures price indices through Gaussian process regressions. (2025). Jin, Bingzi ; Xu, Xiaojie.
    In: Mineral Economics.
    RePEc:spr:minecn:v:38:y:2025:i:1:d:10.1007_s13563-024-00472-9.

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  21. Forecasting crude oil market returns: Enhanced moving average technical indicators. (2022). Zhang, Yaojie ; Wang, Yudong ; Liu, LI ; Wen, Danyan.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:76:y:2022:i:c:s0301420722000216.

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  22. A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features. (2022). Li, Xiuming ; Sun, Mei ; Mensah, Isaac Adjei ; He, Huizi.
    In: Energy.
    RePEc:eee:energy:v:244:y:2022:i:pa:s0360544221029558.

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  23. Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization. (2022). Karasu, Sekin ; Altan, Ayta.
    In: Energy.
    RePEc:eee:energy:v:242:y:2022:i:c:s0360544221032138.

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  24. A novel class of reliability-based parallel hybridization (RPH) models for time series forecasting. (2022). Hajirahimi, Zahra ; Etemadi, Sepideh ; Khashei, Mehdi.
    In: Chaos, Solitons & Fractals.
    RePEc:eee:chsofr:v:156:y:2022:i:c:s0960077922000911.

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  25. 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. (2022). Wang, Xuerui ; Li, Xiangyu.
    In: Applied Energy.
    RePEc:eee:appene:v:328:y:2022:i:c:s0306261922014519.

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  26. The Interdependencies between Economic Growth, Energy Consumption and Pollution in Europe. (2021). Cplescu, Raluca Dana ; Tvaronaviien, Manuela ; Dobrin, Cosmin ; Androniceanu, Ane-Mari.
    In: Energies.
    RePEc:gam:jeners:v:14:y:2021:i:9:p:2577-:d:547046.

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  27. A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities. (2021). Drachal, Krzysztof ; Pawowski, Micha.
    In: Economies.
    RePEc:gam:jecomi:v:9:y:2021:i:1:p:6-:d:483079.

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  28. Short-term forecasting of natural gas prices by using a novel hybrid method based on a combination of the CEEMDAN-SE-and the PSO-ALS-optimized GRU network. (2021). Yuan, Shan ; Cheng, Ming ; Cao, Junxing ; Wang, Jun.
    In: Energy.
    RePEc:eee:energy:v:233:y:2021:i:c:s036054422101330x.

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  29. A decomposition-ensemble model with regrouping method and attention-based gated recurrent unit network for energy price prediction. (2021). Xu, Kunliang ; Niu, Hongli ; Liu, Cheng.
    In: Energy.
    RePEc:eee:energy:v:231:y:2021:i:c:s0360544221011890.

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  30. Data-driven based machine learning models for predicting the deliverability of underground natural gas storage in salt caverns. (2021). Ali, Aliyuda.
    In: Energy.
    RePEc:eee:energy:v:229:y:2021:i:c:s0360544221008975.

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  31. A novel method for online real-time forecasting of crude oil price. (2021). Zhao, Yuan ; Gong, Xue ; Zhang, Weiguo ; Wang, Chao.
    In: Applied Energy.
    RePEc:eee:appene:v:303:y:2021:i:c:s0306261921009648.

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  32. Multi-source Model of Heterogeneous Data Analysis for Oil Price Forecasting. (2021). Baboshkin, Pavel ; Uandykova, Mafura.
    In: International Journal of Energy Economics and Policy.
    RePEc:eco:journ2:2021-02-46.

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  33. Forecasting Crude Oil Price Using Event Extraction. (2021). Huang, Xiaohong ; Liu, Jiangwei.
    In: Papers.
    RePEc:arx:papers:2111.09111.

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  34. A novel hybrid model for forecasting crude oil price based on time series decomposition. (2020). Abdollahi, Hooman.
    In: Applied Energy.
    RePEc:eee:appene:v:267:y:2020:i:c:s030626192030547x.

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