The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Hybrid neural network models for hydrologic time series forecasting
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Citations
Cites
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Cited by
A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data
Babu, C. N., & Reddy, B. E. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.05.028 · Cited by 503
A neural network ensemble method with jittered training data for time series forecasting
Zhang, G. P. (2007) · Information Sciences · doi:10.1016/j.ins.2007.06.015 · Cited by 196
Neural network modeling of hydrological systems: A review of implementation techniques
Oyebode, O., & Stretch, D. (2019) · Natural Resource Modeling · doi:10.1111/nrm.12189 · Cited by 111
Karami, A. (2015) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2015.05.017 · Cited by 29
ML for Flood Forecasting at Scale
Nevo, S., Anisimov, V., Elidan, G., El-Yaniv, R., Giencke, P., Gigi, Y., Hassidim, A., Moshe, Z., Schlesinger, M., Shalev, G., et al. (2019) · arXiv · doi:10.48550/arxiv.1901.09583 · Cited by 23
Metadata
- Authors
- Jain, A., & Kumar, A. M.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2007-03
- Volume
- 7
- Issue
- 2
- Pages
- 585-592
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2080690725
- Cited by
- 465
- References
- 2
- FWCI
- 21.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Jain, A., & Kumar, A. M. (2007). Hybrid neural network models for hydrologic time series forecasting. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2006.03.002
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.
