MOEA/D-DE based bivariate control sequence optimization of a variable-rate fertilizer applicator

•An improved GRNN was proposed to improve the fertilization rate prediction model.•A three-objective bivariate fertilization-rate optimization model was developed.•MOEA/D-DE algorithm was proposed to optimize the control sequence. To realize precise control for a bivariate control system of a variab...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Computers and electronics in agriculture Ročník 167; s. 105063
Hlavní autori:	Zhang, Jiqin, Liu, Gang, Luo, Chengming, Hu, Hao, Huang, Jiayun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 01.12.2019 Elsevier BV
Predmet:	Algorithms applicators Bivariate analysis Coefficient of variation Differential evolution (DE) Evolutionary algorithms Fertilization fertilizers General Regression Neural Network (GRNN) General regression neural networks Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) Multiple objective analysis Optimal control Optimization Precision agriculture Response time Shafts (machine elements) Variable-rate fertilization Precision agriculture General Regression Neural Network (GRNN) Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) Variable-rate fertilization Differential evolution (DE)
ISSN:	0168-1699, 1872-7107
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!