Opportunity ID: 327815
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | W81EWF-20-SOI-0025 |
| Funding Opportunity Title: | Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers’ Reservoir Sedimentation Information (RSI) Database |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Cooperative Agreement |
| Category of Funding Activity: | Science and Technology and other Research and Development |
| Category Explanation: | – |
| Expected Number of Awards: | 1 |
| Assistance Listings: | 12.630 — Basic, Applied, and Advanced Research in Science and Engineering |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 3 |
| Posted Date: | Jun 22, 2020 |
| Last Updated Date: | Aug 10, 2020 |
| Original Closing Date for Applications: | Aug 15, 2020 |
| Current Closing Date for Applications: | Aug 24, 2020 |
| Archive Date: | Sep 23, 2020 |
| Estimated Total Program Funding: | – |
| Award Ceiling: | $40,000 |
| Award Floor: | $0 |
Eligibility
| Eligible Applicants: | Others (see text field entitled “Additional Information on Eligibility” for clarification) |
| Additional Information on Eligibility: | This opportunity is restricted to non-federal partners of the Great Rivers Cooperative Ecosystems Studies Unit (CESU) |
Additional Information
| Agency Name: | Dept. of the Army — Corps of Engineers |
| 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. |
| Link to Additional Information: | – |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
Chelsea M Whitten
Grants Officer Phone 601-634-4679 Email:chelsea.m.whitten@usace.army.mil |
Version History
| Version | Modification Description | Updated Date |
|---|---|---|
| Extend close date | Aug 10, 2020 | |
| Change close date | Jun 22, 2020 | |
| Jun 22, 2020 |
DISPLAYING: Synopsis 3
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | W81EWF-20-SOI-0025 |
| Funding Opportunity Title: | Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers’ Reservoir Sedimentation Information (RSI) Database |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Cooperative Agreement |
| Category of Funding Activity: | Science and Technology and other Research and Development |
| Category Explanation: | – |
| Expected Number of Awards: | 1 |
| Assistance Listings: | 12.630 — Basic, Applied, and Advanced Research in Science and Engineering |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 3 |
| Posted Date: | Jun 22, 2020 |
| Last Updated Date: | Aug 10, 2020 |
| Original Closing Date for Applications: | Aug 15, 2020 |
| Current Closing Date for Applications: | Aug 24, 2020 |
| Archive Date: | Sep 23, 2020 |
| Estimated Total Program Funding: | – |
| Award Ceiling: | $40,000 |
| Award Floor: | $0 |
Eligibility
| Eligible Applicants: | Others (see text field entitled “Additional Information on Eligibility” for clarification) |
| Additional Information on Eligibility: | This opportunity is restricted to non-federal partners of the Great Rivers Cooperative Ecosystems Studies Unit (CESU) |
Additional Information
| Agency Name: | Dept. of the Army — Corps of Engineers |
| 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. |
| Link to Additional Information: | – |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
Chelsea M Whitten
Grants Officer Phone 601-634-4679 Email:chelsea.m.whitten@usace.army.mil |
DISPLAYING: Synopsis 2
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | W81EWF-20-SOI-0025 |
| Funding Opportunity Title: | Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers’ Reservoir Sedimentation Information (RSI) Database |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Cooperative Agreement |
| Category of Funding Activity: | Science and Technology and other Research and Development |
| Category Explanation: | – |
| Expected Number of Awards: | 1 |
| Assistance Listings: | 12.630 — Basic, Applied, and Advanced Research in Science and Engineering |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 2 |
| Posted Date: | Jun 22, 2020 |
| Last Updated Date: | Jun 22, 2020 |
| Original Closing Date for Applications: | – |
| Current Closing Date for Applications: | Aug 14, 2020 |
| Archive Date: | Sep 14, 2020 |
| Estimated Total Program Funding: | – |
| Award Ceiling: | $40,000 |
| Award Floor: | $0 |
Eligibility
| Eligible Applicants: | Others (see text field entitled “Additional Information on Eligibility” for clarification) |
| Additional Information on Eligibility: | This opportunity is restricted to non-federal partners of the Great Rivers Cooperative Ecosystems Studies Unit (CESU) |
Additional Information
| Agency Name: | Dept. of the Army — Corps of Engineers |
| 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. |
| Link to Additional Information: | – |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
Chelsea M Whitten
Grants Officer Phone 601-634-4679 Email:chelsea.m.whitten@usace.army.mil |
DISPLAYING: Synopsis 1
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | W81EWF-20-SOI-0025 |
| Funding Opportunity Title: | Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers’ Reservoir Sedimentation Information (RSI) Database |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Cooperative Agreement |
| Category of Funding Activity: | Science and Technology and other Research and Development |
| Category Explanation: | – |
| Expected Number of Awards: | 1 |
| Assistance Listings: | 12.630 — Basic, Applied, and Advanced Research in Science and Engineering |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 1 |
| Posted Date: | Jun 22, 2020 |
| Last Updated Date: | Jun 22, 2020 |
| Original Closing Date for Applications: | – |
| Current Closing Date for Applications: | Aug 15, 2020 |
| Archive Date: | Sep 14, 2020 |
| Estimated Total Program Funding: | – |
| Award Ceiling: | $40,000 |
| Award Floor: | $0 |
Eligibility
| Eligible Applicants: | Others (see text field entitled “Additional Information on Eligibility” for clarification) |
| Additional Information on Eligibility: | This opportunity is restricted to non-federal partners of the Great Rivers Cooperative Ecosystems Studies Unit (CESU) |
Additional Information
| Agency Name: | Dept. of the Army — Corps of Engineers |
| 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. |
| Link to Additional Information: | – |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
Chelsea M Whitten
Grants Officer Phone 601-634-4679 Email:chelsea.m.whitten@usace.army.mil |
Related Documents
Packages
| Agency Contact Information: | Chelsea M Whitten Grants Officer Phone 601-634-4679 Email: chelsea.m.whitten@usace.army.mil |
| Who Can Apply: | Organization Applicants |
| Assistance Listing Number | Competition ID | Competition Title | Opportunity Package ID | Opening Date | Closing Date | Actions |
|---|---|---|---|---|---|---|
| 12.630 | PKG00262284 | Jun 22, 2020 | Aug 24, 2020 | View |
Package 1
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