Record Details
Modular neural network to predict the distribution of nitrate in ground water using on-ground nitrogen loading and recharge data
DigitalCommons@USU
| Field | Value |
|---|---|
| Title | Modular neural network to predict the distribution of nitrate in ground water using on-ground nitrogen loading and recharge data |
| Creator | Almasri, M. Kaluarachchi, Jagath J. |
| Description | Artificial neural networks have proven to be an attractive mathematical tool to represent complex relationships in many branches of hydrology. Due to this attractive feature, neural networks are increasingly being applied in subsurface modeling where intricate physical processes and lack of detailed field data prevail. In this paper, a methodology using modular neural networks (MNN) is proposed to simulate the nitrate concentrations in an agriculture-dominated aquifer. The methodology relies... |
| Date | 2005-07-01T07:00:00Z |
| Type | text |
| Format | application/pdf |
| Identifier | https://digitalcommons.usu.edu/cee_facpub/1282 info:doi/10.1016/j.envsoft.2004.05.001 https://digitalcommons.usu.edu/context/cee_facpub/article/2282/viewcontent/1_s2.0_S1364815204001185_main.pdf |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact the Institutional Repository Librarian at digitalcommons@usu.edu. |
| Source | Civil and Environmental Engineering Faculty Publications |
| Publisher | Hosted by Utah State University Libraries |
| Subject | Nitrate Nitrogen Ground water Artificial neural network Modular neural network Agriculture Land use GIS Contamination UWRL Civil and Environmental Engineering |
