Artificial neural network modeling for predicting the growth of the microalga Karlodinium veneficum
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An algal digital twin, as an integrated practice, helps to drive data-driven models and ecological sustainability initiatives using big data, IoT, AI and ML, and advanced computing for information gathering and analysis.
“An ADT, as an integrated practice, helps to drive data-driven (DD) models, and ecological sustainability initiatives [15,16] using BD, IoT, AI & ML, and advanced computing for informa tion gathering as well as analysis [17,18].”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [15]
The FBN-based modelling approach is extremely adaptable and multifunctional.
“The FBN-based modelling approach is extremely adaptable and multifunctional.”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [15]
Micronutrients, although present at lower quantities compared to macronutrients, have a significant impact on the growth of microalgae.
“The findings indicate that micronutrients, although present at lower quantities compared to macronutrients, have a significant impact on the growth of microalgae.”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [15]
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- Authors
- García-Camacho, F., López-Rosales, L., Sánchez-Mirón, A., Belarbi, E. H., Chisti, Y., & Molina-Grima, E.
- Affiliations
- University of Almería (ES)
- Corresponding author
- García-Camacho, F.
- Venue
- Algal Research
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 14
- Pages
- 58-64
- ISSN
- 2211-9264 (ISSN-L)
- OpenAlex
- W2232774222
- Cited by
- 67
- References
- 32
- Citations by year
- 2026: 8 · 2025: 5 · 2024: 10 · 2023: 4 · 2022: 6 · 2021: 7 · 2020: 9 · 2019: 6 · 2018: 3 · 2017: 8 · 2016: 1
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Algal Research (publishedVersion)
- Funders
- Ministry of Economy and Competitiveness (SAF2011-28883-C03-02)
- European Regional Development Fund Program (CTQ2014-55888-C3-02)
- University of Almería, Spain
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Keywords
- Karlodinium veneficum, feedforward backpropagation neural network, culture medium composition, nutrient interactions, macronutrients, initial cell concentration, culture duration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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