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Can Machine Learning classifiers be used to regulate nutrients using small training datasets for aquaponic irrigation?: A comparative analysis.
Dhal, Sambandh Bhusan; Bagavathiannan, Muthukumar; Braga-Neto, Ulisses; Kalafatis, Stavros.
Affiliation
  • Dhal SB; Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.
  • Bagavathiannan M; Department of Soil and Crop Sciences, Texas A&M University, College Station, Texas, United States of America.
  • Braga-Neto U; Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.
  • Kalafatis S; Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.
PLoS One ; 17(8): e0269401, 2022.
Article in En | MEDLINE | ID: mdl-35972941
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nutrients / Machine Learning Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2022 Document type: Article Affiliation country: United States Country of publication: United States
Fulltext
Add to My VHL
Print
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nutrients / Machine Learning Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2022 Document type: Article Affiliation country: United States Country of publication: United States