The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting
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Citations
Cites
Time Series Analysis: Forecasting and Control
Geurts, M., Box, G. E. P., & Jenkins, G. M. (1977) · Journal of Marketing Research · doi:10.2307/3150485 · Cited by 19,186
Time Series Analysis: Forecasting and Control.
Anderson, O. D., Box, G. E. P., & Jenkins, G. M. (1978) · The Statistician · doi:10.2307/2988198 · Cited by 5,298
Time Series Analysis, Forecasting and Control.
Kendall, M. G., Box, G. E. P., & Jenkins, G. M. (1971) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344246 · Cited by 2,771
Electric load forecasting using an artificial neural network
Park, D.-C., El-Sharkawi, M. A., Marks, R. J., Atlas, L., & Damborg, M. J. (1991) · IEEE Transactions on Power Systems · doi:10.1109/59.76685 · Cited by 1,440
A regression-based approach to short-term system load forecasting
Papalexopoulos, A. D., & Hesterberg, T. C. (1990) · IEEE Transactions on Power Systems · doi:10.1109/59.99410 · Cited by 823
Short-term load forecasting using an artificial neural network
Lee, K. Y., Cha, Y. T., & Park, J. H. (1992) · IEEE Transactions on Power Systems · doi:10.1109/59.141695 · Cited by 602
The Time Series Approach to Short Term Load Forecasting
Hagan, M. T., & Behr, S. M. (1987) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.1987.4335210 · Cited by 546
Short-Term Load Forecasting Using General Exponential Smoothing
Christiaanse, W. (1971) · IEEE Transactions on Power Apparatus and Systems · doi:10.1109/tpas.1971.293123 · Cited by 500
Cited by
Bouktif, S., Fiaz, A., Ouni, A., & Serhani, M. (2018) · Energies · doi:10.3390/en11071636 · Cited by 915
Electric load forecasting: Literature survey and classification of methods
Alfares, H. K., & Nazeeruddin, M. (2002) · International Journal of Systems Science · doi:10.1080/00207720110067421 · Cited by 743
Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach
Weron, R. (2006) · doi:10.1002/9781118673362 · Cited by 708
On recent advances in PV output power forecast
Raza, M. Q., Nadarajah, M., & Ekanayake, C. (2016) · Solar Energy · doi:10.1016/j.solener.2016.06.073 · Cited by 544
Load forecasting, dynamic pricing and DSM in smart grid: A review
Khan, A. R., Mahmood, A., Safdar, A., Khan, Z. A., & Khan, N. A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.10.117 · Cited by 469
Metadata
- Authors
- Chen, J.-F., Wang, W.-M., & Huang, C.-M.
- Venue
- Electric Power Systems Research
- Publisher
- Elsevier BV
- Published
- 1995-09
- Volume
- 34
- Issue
- 3
- Pages
- 187-196
- ISSN
- 0378-7796 (ISSN-L)
- OpenAlex
- W1967690950
- Cited by
- 253
- References
- 8
- FWCI
- 0.48
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- This page
- CoChat. (2026). Citation check: Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting. https://app.cochat.ai/papers/10.1016/0378-7796(95)00977-1
- The paper
- Chen, J.-F., Wang, W.-M., & Huang, C.-M. (1995). Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting. Electric Power Systems Research. https://doi.org/10.1016/0378-7796(95)00977-1
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.
