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researcher

Daniel Rivero

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.AI1
ORCID 0000-0001-8245-3094

identity via Semantic Scholar / OpenAlex

most citedHybrid Machine Learning techniques in the management of harmful algal blooms impact

15 citations · 21 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024

Harmful algal bloom forecasting. A comparison between stream and batch learning

Andres Molares-Ulloa, Elisabet Rocruz, Daniel Rivero +4

Diarrhetic Shellfish Poisoning (DSP) is a global health threat arising from shellfish contaminated with toxins produced by dinoflagellates. The condition, with its widespread incid…

cs.LG2024★ 15 cited

Hybrid Machine Learning techniques in the management of harmful algal blooms impact

Andres Molares-Ulloa, Daniel Rivero, Jesus Gil Ruiz +2

Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filte…

cs.AI2024★ 6 cited

Machine Learning in management of precautionary closures caused by lipophilic biotoxins

Andres Molares-Ulloa, Enrique Fernandez-Blanco, Alejandro Pazos +1

Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galic…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.