The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Optimization of neural networks for precipitation analysis in a humid region to detect drought and wet year alarms
Abstract
In this study, annual precipitation was forecast by coding in MATLAB software environment based on a non‐linear autoregressive neural network (NARNN), non‐linear input–output (NIO) and NARNN with exogenous input (NARNNX). Historical precipitation data (27 precipitation gauge stations located in Gilan, Iran) were used as two 21 year sets from 1968 to 1988 and from 1989 to 2009 for calibration and testing of the networks, respectively. Results showed that the accuracy of the NARNNX was better than that of the NARNN and NIO, based on r values. However, performance of the networks was not satisfactory because the number of neurons in the hidden layer and the roles of training, validation and testing phases were lacking flexibility and change. Optimization of the number of neurons in the hidden layer and the determination of the best role among the different phases led to improvement of network accuracy. The r values were <0.73 only for five stations in the optimized NARNN and <0.74 only for those stations with optimized NIO.
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Maier, H. R., Jain, A., Dandy, G. C., & Sudheer, K. P. (2010) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2010.02.003 · Cited by 871
Valipour, M., Banihabib, M. E., & Behbahani, S. M. (2012) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.11.017 · Cited by 831
Self-citationValipour, M. (2015) · Meteorological Applications · doi:10.1002/met.1491 · Cited by 319
Self-citationSurface irrigation simulation models: a review
Valipour, M., Sefidkouhi, M. A. G., & Eslamian, S. (2015) · International Journal of Hydrology Science and Technology · doi:10.1504/ijhst.2015.069279 · Cited by 188
Self-citationTemporal and spatial variability of annual and seasonal rainfall over Ethiopia
Wagesho, N., Goel, N. K., & Jain, M. K. (2013) · Hydrological Sciences Journal · doi:10.1080/02626667.2012.754543 · Cited by 169
Kişi, Ö., & Shiri, J. (2011) · Water Resources Management · doi:10.1007/s11269-011-9849-3 · Cited by 167
Simulation of open- and closed-end border irrigation systems using SIRMOD
Mahdizadeh Khasraghi, M., Gholami Sefidkouhi, M. A., & Valipour, M. (2015) · Archives of Agronomy and Soil Science · doi:10.1080/03650340.2014.981163 · Cited by 167
Self-citationDrainage, waterlogging, and salinity
Valipour, M. (2014) · Archives of Agronomy and Soil Science · doi:10.1080/03650340.2014.905676 · Cited by 157
Self-citationAgricultural water management in the world during past half century
Valipour, M., Ahmadi, M. Z., Raeini−Sarjaz, M., Sefidkouhi, M. A. G., Shahnazari, A., Fazlola, R., & Darzi‐Naftchali, A. (2014) · Archives of Agronomy and Soil Science · doi:10.1080/03650340.2014.944903 · Cited by 134
Self-citationGeneralized regression neural network in monthly flow forecasting
Ciğizoğlu, H. K. (2005) · Civil Engineering and Environmental Systems · doi:10.1080/10286600500126256 · Cited by 124
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Metadata
- Authors
- Valipour, M.
- Venue
- Meteorological Applications
- Publisher
- Wiley
- Published
- 2015-11-25
- Volume
- 23
- Issue
- 1
- Pages
- 91-100
- ISSN
- 1350-4827 (ISSN-L)
- 1469-8080
- OpenAlex
- W2232732673
- Cited by
- 308
- References
- 15
- FWCI
- 57.90
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
