Artificial Neural Network for Prediction of Total Nitrogen and Phosphorus in US Lakes-Reference-Cited by-同舟云学术

Artificial Neural Network for Prediction of Total Nitrogen and Phosphorus in US Lakes

Published:2019-06 Issue:6 Volume:145 Page:04019032
ISSN:0733-9372
Container-title:Journal of Environmental Engineering
language:en
Short-container-title:J. Environ. Eng.

Author:

Sinshaw Tadesse A.¹,Surbeck Cristiane Q.²,Yasarer Hakan³,Najjar Yacoub⁴

Affiliation:

1. Ph.D. Candidate, Dept. of Civil Engineering, Univ. of Mississippi, Oxford, MS 38677 (corresponding author).

2. Associate Professor and Associate Dean, Dept. of Civil Engineering, Univ. of Mississippi, Oxford, MS 38677.

3. Assistant Professor, Dept. of Civil Engineering, Univ. of Mississippi, Oxford, MS 38677.

4. Professor and Chair, Dept. of Civil Engineering, Univ. of Mississippi, Oxford, MS 38677.

Publisher

American Society of Civil Engineers (ASCE)

Subject

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

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EE.1943-7870.0001528

Reference36 articles.

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3. SWAT: Model Use, Calibration, and Validation

4. Using Multiple Watershed Models to Predict Water, Nitrogen, and Phosphorus Discharges to the Patuxent Estuary1

5. CFR (Code of Federal Regulations). 2018. “Guidelines establishing test procedures for the analysis of pollutants part 136.” Accessed April 12 2018. https://www.ecfr.gov/cgi-bin/text-idx?SID=a6bb8a02b6d783f9356758b5ff0ed106&mc=true&node=pt40.25.136&rgn=div5.

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