OpportunityTitle: Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers&#8217; Reservoir Sedimentation Information (RSI) Database
AdditionalInformationOnEligibility: This opportunity is restricted to non-federal partners of the Great Rivers Cooperative Ecosystems Studies Unit (CESU)
Description: The primary objective is to develop a method to identify erroneous data within the RSI system. Ideally, the investigator(s) will utilize machine learning algorithms to identify anomalies within the dataset. A secondary goal of the study is to use the RSI data, with supplementary data from other available data sources, to develop a machine-learning approach to estimate sedimentation rates. Research tasks should include: identifying appropriate supplemental data from other data sources; 2) identify any patterns and trends in the RSI data; 3) develop a machine-learning method to identify anomalies within the RSI data based on the composite dataset; and 4) develop a machine-learning method for estimating reservoir sedimentation rates.
GrantorContactEmailDescription: Grants Officer
GrantorContactText: Chelsea M Whitten &lt;br/&gt;Grants Officer &lt;br/&gt;Phone 601-634-4679