Application of artificial neural network (ANN) and response surface methodology (RSM) for modeling and optimization of the contact angle of rice leaf surfaces

• Autorzy: Zhang J. , Lin G. , Yin X. , Zeng J. , Wen S. , Lan Y.
• Języki publikacji: EN

Abstrakty

EN

• Wydawca: -
• Czasopismo: Acta Physiologiae Plantarum
• Rocznik: 2020
• Tom: 42
• Numer: 04
• Opis fizyczny: Article 51 [15p.], fig.,ref.

Twórcy

autor

Zhang J.

• College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
• National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China

autor

Lin G.

• College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
• National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China

autor

Yin X.

• National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China
• Engineering College, South China Agricultural University, Guangzhou 510642, China

autor

Zeng J.

• College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
• National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China

autor

Wen S.

• National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China
• Engineering Foundation Teaching and Training Center, South China Agricultural University, Guangzhou 510642, China

autor

Lan Y.

• National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangzhou 510642, China
• Engineering College, South China Agricultural University, Guangzhou 510642, China

Identyfikatory

DOI

10.1007/s11738-020-03040-0