Response Surfaces Method and Artificial Intelligence Approaches for Modeling the Effects of Environmental Factors on Chlorophyll a in <i>Isochrysis galbana</i>.

Zhang, Linlin; Liu, Jie; Shen, Xin; Li, Shuangwei; Li, Wenfang; Xiao, Xinfeng

Response Surfaces Method and Artificial Intelligence Approaches for Modeling the Effects of Environmental Factors on Chlorophyll a in Isochrysis galbana.

Zhang, Linlin; Liu, Jie; Shen, Xin; Li, Shuangwei; Li, Wenfang; Xiao, Xinfeng.

Afiliación

Zhang L; College of Chemistry and Environment Engineering, Shandong University of Science & Technology, Qingdao 266510, China.
Liu J; College of Chemistry and Environment Engineering, Shandong University of Science & Technology, Qingdao 266510, China.
Shen X; College of Chemistry and Environment Engineering, Shandong University of Science & Technology, Qingdao 266510, China.
Li S; College of Chemistry and Environment Engineering, Shandong University of Science & Technology, Qingdao 266510, China.
Li W; College of Chemistry and Environment Engineering, Shandong University of Science & Technology, Qingdao 266510, China.
Xiao X; College of Chemistry and Environment Engineering, Shandong University of Science & Technology, Qingdao 266510, China.

Microorganisms ; 11(8)2023 Jul 25.

Article en En | MEDLINE | ID: mdl-37630435

Palabras clave

RSM; artificial intelligence algorithms; chlorophyll a; condition optimization

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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Microorganisms Año: 2023 Tipo del documento: Article País de afiliación: China

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