Modelling biochemical oxygen demand using improved neuro-fuzzy approach by marine predators algorithm.

Adnan, Rana Muhammad; Dai, Hong-Liang; Kisi, Ozgur; Heddam, Salim; Kim, Sungwon; Kulls, Christoph; Zounemat-Kermani, Mohammad

Adnan, Rana Muhammad; Dai, Hong-Liang; Kisi, Ozgur; Heddam, Salim; Kim, Sungwon; Kulls, Christoph; Zounemat-Kermani, Mohammad.

Afiliación

Adnan RM; School of Economics and Statistics, Guangzhou University, Guangzhou, 510006, China.
Dai HL; School of Economics and Statistics, Guangzhou University, Guangzhou, 510006, China.
Kisi O; Department of Civil Engineering, Lübeck University of Applied Science, 23562, Lubeck, Germany. ozgur.kisi@th-luebeck.de.
Heddam S; Department of Civil Engineering, School of Technology, Ilia State University, 0162, Tbilisi, Georgia. ozgur.kisi@th-luebeck.de.
Kim S; Faculty of Science, Agronomy Department, Hydraulics Division University, 20 Août 1955, Route El Hadaik, 21024, Skikda, BP 26, Algeria.
Kulls C; Department of Railroad Construction and Safety Engineering, Dongyang University, Yeongju, 36040, Republic of Korea.
Zounemat-Kermani M; Department of Civil Engineering, Lübeck University of Applied Science, 23562, Lubeck, Germany.

Environ Sci Pollut Res Int ; 30(41): 94312-94333, 2023 Sep.

Article en En | MEDLINE | ID: mdl-37531049

Asunto(s)

Algoritmos; Lógica Difusa; Calidad del Agua; Análisis de la Demanda Biológica de Oxígeno; Oxígeno/análisis

Palabras clave

Biochemical oxygen demand; Marine predators algorithm; Neuro-fuzzy; Prediction; Water quality

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Lógica Difusa Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Pollut Res Int Asunto de la revista: SAUDE AMBIENTAL / TOXICOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: China

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