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Exploring the effects of different combinations of predictor variables for the treatment of wastewater by microalgae and biomass production
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“DT algorithms can efficiently assess extensive microalgae datasets and identify optimal combinations of predictor factors for constructing new trials.”
From Reinvigorating algal cultivation for biomass production with digital twin technology - a smart sustainable infrastructure (2024) · cites this paper as [89]
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Metadata
- Authors
- Singh, V., & Mishra, V.
- Affiliations
- Indian Institute of Technology BHU (IN)
- Corresponding author
- Mishra, Vishal
- Venue
- Biochemical Engineering Journal
- Publisher
- Elsevier BV
- Published
- 2021-10
- Volume
- 174
- Pages
- 108129
- ISSN
- 1369-703X (ISSN-L)
- OpenAlex
- W3177594093
- Cited by
- 46
- References
- 295
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 10 · 2023: 12 · 2022: 6 · 2021: 1
- FWCI
- 1.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Biochemical Engineering Journal (publishedVersion)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Environmental Science › Waste Management and Disposal › Wastewater Treatment and Reuse
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Keywords
- microalgae-based wastewater treatment, microalgae cultivation, decision tree analysis, nitrogen removal, phosphorus removal, resource recovery
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