Training Artificial Neural Networks to Perform Rainfall Disaggregation-Reference-Cited by-同舟云学术

Training Artificial Neural Networks to Perform Rainfall Disaggregation

Published:2001-01 Issue:1 Volume:6 Page:43-51
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Burian Steven J.¹²³⁴,Durrans S. Rocky¹²³⁴,Nix Stephan J.¹²³⁴,Pitt Robert E.¹²³⁴

Affiliation:

1. Asst. Prof., Dept. of Civ. Engrg., 4190 Bell Engrg. Ctr., Univ. of Arkansas, Fayetteville, AR 72701. E-mail: sburian@engr.uark.edu

2. Assoc. Prof., Dept. of Civ. and Envir. Engrg., Univ. of Alabama, Tuscaloosa, AL 35487.

3. Prof. and Chair, Dept. of Civ. and Envir. Engrg., Northern Arizona Univ., Flagstaff, AZ 86011.

4. Prof., Dept. of Civ. and Envir. Engrg., Univ. of Alabama at Birmingham, Birmingham, AL 35294.

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%291084-0699%282001%296%3A1%2843%29

Reference20 articles.

1. Rainfall Disaggregation Using Artificial Neural Networks

2. Connolly R. D. Schirmer J. and Dunn P. K. ( 1998). “A daily rainfall disaggregation model.” Agric. and Forest Meteorology 92 105–117.

3. Dowla F. U. and Rogers L. L. ( 1995). Solving problems in environmental engineering and geosciences with artificial neural networks MIT Press Cambridge Mass.

4. Durrans S. R. et al. ( 1999). “Polynomial-based disaggregation of hourly rainfall for continuous hydrologic simulation.” Am. Water Resour. Assn. 35(5) 1213–1221.

5. Foufoula-Georgiou E. and Krajewski W. F. ( 1995). “Recent advances in rainfall modeling estimation and forecasting.” Review of geophysics U.S. Nat. Rep. to Int. Union of Geodesy and Geophysics 991–1994 1125–1137.

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