The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
A novel hybrid method for crude oil price forecasting
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Citations
Cites
Generalized autoregressive conditional heteroskedasticity
Bollerslev, T. (1986) · Journal of Econometrics · doi:10.1016/0304-4076(86)90063-1 · Cited by 22,254
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Bertsekas, D. P. (1997) · Journal of the Operational Research Society · doi:10.1038/sj.jors.2600425 · Cited by 11,726
Least Squares Support Vector Machine Classifiers
Suykens, J. A. K., & Vandewalle, J. (1999) · Neural Processing Letters · doi:10.1023/a:1018628609742 · Cited by 9,362
ENSEMBLE EMPIRICAL MODE DECOMPOSITION: A NOISE-ASSISTED DATA ANALYSIS METHOD
WU, Z., & HUANG, N. E. (2009) · Advances in Adaptive Data Analysis · doi:10.1142/s1793536909000047 · Cited by 8,715
Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
Keerthi, S. S., & Lin, C.-J. (2003) · Neural Computation · doi:10.1162/089976603321891855 · Cited by 1,622
Comparing support vector machines with Gaussian kernels to radial basis function classifiers
Scholkopf, B., Sung, K.-K., Burges, C. J. C., Girosi, F., Niyogi, P., Poggio, T., & Vapnik, V. (1997) · IEEE Transactions on Signal Processing · doi:10.1109/78.650102 · Cited by 1,400
Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability
(1951) · University of California Press eBooks · doi:10.1525/9780520411586 · Cited by 806
Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm
Yu, L., Wang, S., & Lai, K. K. (2008) · Energy Economics · doi:10.1016/j.eneco.2008.05.003 · Cited by 713
Modeling and forecasting petroleum futures volatility
Sadorsky, P. (2006) · Energy Economics · doi:10.1016/j.eneco.2006.04.005 · Cited by 478
Cited by
A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting
Zhu, B., Ye, S., Wang, P., He, K., Zhang, T., & Wei, Y.-M. (2018) · Energy Economics · doi:10.1016/j.eneco.2017.12.030 · Cited by 236
Metadata
- Authors
- Zhang, J.-L., Zhang, Y.-J., & Zhang, L.
- Venue
- Energy Economics
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 49
- Pages
- 649-659
- ISSN
- 0140-9883 (ISSN-L)
- OpenAlex
- W1978266801
- Cited by
- 272
- References
- 35
- FWCI
- 29.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, J.-L., Zhang, Y.-J., & Zhang, L. (2015). A novel hybrid method for crude oil price forecasting. Energy Economics. https://doi.org/10.1016/j.eneco.2015.02.018
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
