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more general categories information about this item Calendar Year Calendar Year Year (337475) 2010 (38932) Geographical Locations Geographical Locations Asia (16685) East Asia (10715) Taiwan (717) Natural Resources, Earth and Environmental Sciences Natural Resources, Earth and Environmental Sciences geology (23343) geomorphology (10939) landforms (9516) coasts (1583) hydrology (18092) water (12151) groundwater (2536) water table (978) high water table (79) natural resource management (11559) water management (3752) hydraulic structures (905) wells (747) Physical and Chemical Sciences Physical and Chemical Sciences chemical substances (129118) elements (30672) nonmetallic elements (20442) arsenic (962) trace elements (7005) arsenic (962) Reference Types Reference Types Journal (337546) Research, Technology and Engineering Research, Technology and Engineering engineering (9759) manmade structures (4337) hydraulic structures (905) wells (747) geospatial science and technology (2769) spatial data (611) mathematics and statistics (33406) mathematical models (6495) nonlinear models (896) neural networks (701) statistics (23850) statistical analysis (13399) principal component analysis (1576) methodology (66114) monitoring (4857) research (30526) research methods (29174) model validation (1195) support systems and models (27487) models (27236) mathematical models (6495) nonlinear models (896) neural networks (701) Abstract of Article: Will be presented in next release Date Last Accessed: Accessed January 20, 2015 Title of Article: Artificial neural networks for estimating regional arsenic concentrations in a blackfoot disease area in Taiwan Author(s) of Article: Will be identified in next release Citation: Journal of hydrology 2010 v.388 no.1-2 pp. 65-76 Click to View: (Click to View) Date of Publication: 2010 Location of Article: http://pubag.nal.usda.gov/pubag/article.xhtml?id=435118 Name of Publication: Journal of hydrology Publishing Company: Will be identified in next release Accession Number: 72235
