The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data
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Citations
Cites
Neural Networks And Learning Machines
Haykin, S. (2010) · Cited by 6,609
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 forecasting using a hybrid ARIMA and neural network model
Zhang, G. P. (2003) · Neurocomputing · doi:10.1016/s0925-2312(01)00702-0 · Cited by 4,428
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
On the meaning and use of kurtosis.
DeCarlo, L. T. (1997) · Psychological Methods · doi:10.1037//1082-989x.2.3.292 · Cited by 1,755
ARIMA models to predict next-day electricity prices
Contreras, J., Espinola, R., Nogales, F. J., & Conejo, A. J. (2003) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2002.804943 · Cited by 1,553
Day-Ahead Electricity Price Forecasting Using the Wavelet Transform and ARIMA Models
Conejo, A. J., Plazas, M. A., Espinola, R., & Molina, A. B. (2005) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2005.846054 · Cited by 986
ARIMA Models to Predict Next-Day Electricity Prices
Contreras, J., Espinola, R., Nogales, F. J., & Conejo, A. J. (2002) · IEEE Power Engineering Review · doi:10.1109/mper.2002.4312577 · Cited by 928
A novel hybridization of artificial neural networks and ARIMA models for time series forecasting
Khashei, M., & Bijari, M. (2011) · Applied Soft Computing · doi:10.1016/j.asoc.2010.10.015 · Cited by 821
A hybrid neural network and ARIMA model for water quality time series prediction
Ömer Faruk, D. (2010) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2009.09.015 · Cited by 707
Cited by
Stock selection with random forest: An exploitation of excess return in the Chinese stock market
Tan, Z., Yan, Z., & Zhu, G. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e02310 · Cited by 107
Automated detection-in-depth in industrial control systems
Jadidi, Z., Foo, E., Hussain, M., & Fidge, C. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-08001-6 · Cited by 31
Metadata
- Authors
- Babu, C. N., & Reddy, B. E.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 23
- Pages
- 27-38
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W1989130706
- Cited by
- 503
- References
- 24
- FWCI
- 28.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data. https://app.cochat.ai/papers/10.1016/j.asoc.2014.05.028
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- Babu, C. N., & Reddy, B. E. (2014). A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2014.05.028
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.
