Developing Rainfall Intensity-Duration-Frequency Curves for Alabama under Future Climate Scenarios Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Developing Rainfall Intensity-Duration-Frequency Curves for Alabama under Future Climate Scenarios Using Artificial Neural Networks

Published:2014-11 Issue:11 Volume:19 Page:04014022
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Mirhosseini Golbahar¹,Srivastava Puneet²,Fang Xing³

Affiliation:

1. Research Fellow, Auburn Univ., Auburn Research Park, 559 Devall Dr. CASIC Building, Office 207, Auburn, AL 36832 (corresponding author).

2. Professor, Ecological Engineering, Auburn Univ., 206 Tom E. Corley Building, Auburn, AL 36849.

3. Professor, Dept. of Civil Engineering, Auburn Univ., 229 Harbert Engineering Center, Auburn, AL 36849-5337.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0000962

Reference42 articles.

1. Simple Parameter Estimation Technique for Three-Parameter Generalized Extreme Value Distribution

2. Input determination for neural network models in water resources applications. Part 1—background and methodology

3. Rainfall Disaggregation Using Artificial Neural Networks

4. Training Artificial Neural Networks to Perform Rainfall Disaggregation

5. Hydrological modelling using artificial neural networks

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