The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Rainfall–runoff modeling using artificial neural network coupled with singular spectrum analysis
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Citations
Cites
River flow forecasting through conceptual models part I — A discussion of principles
Nash, J. E., & Sutcliffe, J. V. (1970) · Journal of Hydrology · doi:10.1016/0022-1694(70)90255-6 · Cited by 23,674
Pattern Recognition with Fuzzy Objective Function Algorithms
Bezdek, J. C. (1981) · doi:10.1007/978-1-4757-0450-1 · Cited by 9,881
Independent coordinates for strange attractors from mutual information
Fraser, A. M., & Swinney, H. L. (1986) · Physical Review A · doi:10.1103/physreva.33.1134 · Cited by 4,606
Evaluating the use of “goodness‐of‐fit” Measures in hydrologic and hydroclimatic model validation
Legates, D. R., & McCabe, G. J. (1999) · Water Resources Research · doi:10.1029/1998wr900018 · Cited by 4,591
Gunst, R. F. (1999) · Technometrics · doi:10.1080/00401706.1999.10485680 · Cited by 4,002
Maier, H. R., & Dandy, G. C. (2000) · Environmental Modelling & Software · doi:10.1016/s1364-8152(99)00007-9 · Cited by 2,377
Artificial Neural Network Modeling of the Rainfall‐Runoff Process
Hsu, K., Gupta, H. V., & Sorooshian, S. (1995) · Water Resources Research · doi:10.1029/95wr01955 · Cited by 1,515
Artificial Neural Networks in Hydrology. II: Hydrologic Applications
ASCE Task Committee on Application of Artificial Neural Networks in Hydrology (2000) · Journal of Hydrologic Engineering · doi:10.1061/(asce)1084-0699(2000)5:2(124 · Cited by 1,339
Hydrologic Analysis and Design
McCuen, R. H. (1989) · Medical Entomology and Zoology · Cited by 917
Hydrological modelling using artificial neural networks
Dawson, C. W., & Wilby, R. L. (2001) · Progress in Physical Geography: Earth and Environment · doi:10.1177/030913330102500104 · Cited by 903
Cited by
Evapotranspiration evaluation models based on machine learning algorithms—A comparative study
Granata, F. (2019) · Agricultural Water Management · doi:10.1016/j.agwat.2019.03.015 · Cited by 361
He, Z., Wen, X., Liu, H., & Du, J. (2014) · Journal of Hydrology · doi:10.1016/j.jhydrol.2013.11.054 · Cited by 332
Tongal, H., & Booij, M. J. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.07.004 · Cited by 267
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
Metadata
- Authors
- Wu, C. L., & Chau, K. W.
- Venue
- Journal of Hydrology
- Publisher
- Elsevier BV
- Published
- 2011-03
- Volume
- 399
- Issue
- 3-4
- Pages
- 394-409
- ISSN
- 0022-1694 (ISSN-L)
- OpenAlex
- W2022754289
- Cited by
- 360
- References
- 45
- FWCI
- 9.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Wu, C. L., & Chau, K. W. (2011). Rainfall–runoff modeling using artificial neural network coupled with singular spectrum analysis. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2011.01.017
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.
