Precision agriculture management based on a surrogate model assisted multiobjective algorithmic framework.

ABSTRACT: Sustainable intensification needs to optimize irrigation and fertilization strategies while increasing crop yield. To enable more precision and effective agricultural management, a bi-level screening and bi-level optimization framework is proposed. Irrigation and fertilization dates are obtained by upper-level screening and upper-level optimization. Subsequently, due to the complexity of the problem, the lower-level optimization uses a data-driven evolutionary algorithm, which combines the fast non-dominated sorting genetic algorithm (NSGA-II), surrogate-assisted model of radial basis function and Decision Support System for Agrotechnology Transfer to handle the expensive objective problem and produce a set of optimal solutions representing a trade-off between conflicting objectives. Then,

SUBMITTER: Cheng D 

PROVIDER: S-EPMC9860027 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature