Comparison between response surface models and artificial neural networks in hydrologic forecasting
Developing an efficient and accurate hydrologic forecasting model is crucial to managing water resources and flooding issues. In this study, response surface (RS) models including multiple linear regression (MLR), quadratic response surface (QRS), and nonlinear response surface (NRS) were applied to...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/79536 http://hdl.handle.net/10220/19646 |
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| Institution: | Nanyang Technological University |
| Language: | English |