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Using machine learning in Minnesota's StreamStats to predict fluvial sediment / by Joel T. Groten, [and six others].
Connect to full text Available online
View online- Format:
- Book
- Government document
- Author/Creator:
- Groten, Joel T., author.
- Series:
- Fact sheet (Geological Survey (U.S.)) ; 2025-3005.
- Fact sheet, 2327-6932 ; 2025-3005
- Language:
- English
- Subjects (All):
- Sediment transport--Minnesota.
- Sediment transport.
- Sediment control--Minnesota.
- Sediment control.
- Suspended sediments--Minnesota.
- Suspended sediments.
- Streamflow--Minnesota.
- Streamflow.
- Machine learning.
- Physical Description:
- 1 online resource (4 unnumbered pages) : color illustrations, color map.
- Place of Publication:
- [Reston, Virginia] : U.S. Department of the Interior, U.S. Geological Survey, 2025.
- Notes:
- In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).
- "Prepared in cooperation with the Minnesota Pollution Control Agency."
- "January 2025."
- "By Joel T. Groten, J. William Lund, Erin N. Coenen, Andrea S. Medenblik, Harper N. Wavra, Mike Kennedy, and Gregory D. Johnson"--Page 4.
- Includes bibliographical references (page 4).
- Description based on online resource; title from caption (USGS, viewed March 10, 2025).
- OCLC:
- 1516213078
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