MODELING NITRATE CONCENTRATION IN GROUND WATER USING REGRESSION AND NEURAL NETWORKS

Nacha Ramasamy, Palaniappa Krishnan, John C. Bernard () and William F. Ritter

No 15825, Staff Papers from University of Delaware, Department of Food and Resource Economics

Abstract: Nitrate concentration in ground water is a major problem in specific agricultural areas. Using regression and neural networks, this study models nitrate concentration in ground water as a function of iron concentration in ground water, season and distance of the well from a poultry house. Results from both techniques are comparable and show that the distance of the well from a poultry house has a significant effect on nitrate concentration in groundwater.

Keywords: Environmental Economics and Policy; Livestock Production/Industries (search for similar items in EconPapers)
Date: 2003
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://purl.umn.edu/15825 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:ags:udelsp:15825

Access Statistics for this paper

More papers in Staff Papers from University of Delaware, Department of Food and Resource Economics
Contact information at EDIRC.
Series data maintained by AgEcon Search ().