Comparison of four learning-based methods for predicting groundwater redox status

Volume: 580, Pages: 124200 - 124200
Published: Jan 1, 2020
Abstract
Knowing the location where groundwater denitrification occurs, or by proxy the groundwater redox status (oxic, mixed, and anoxic), is valuable information for assessing and managing potential agricultural land-use impacts on freshwater quality. We compare the efficacy of supervised (Linear Discriminant Analysis LDA; Boosted Regression Trees, BRT; and Random Forest, RF) and unsupervised (Modified Self-Organizing Map, MSOM) learning-based methods...
Paper Details
Title
Comparison of four learning-based methods for predicting groundwater redox status
Published Date
Jan 1, 2020
Volume
580
Pages
124200 - 124200
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.