Abstract
The delimitation of permanent basic farmland is essentially a multi-objective optimization problem. The traditional demarcation methods cannot simultaneously take into account the requirements of cultivated land quality and the spatial layout of permanent basic farmland, and it cannot balance the relationship between agriculture and urban development. This paper proposed a multi-objective permanent basic farmland delimitation model based on an immune particle swarm optimization algorithm. The general rules for delineating the permanent basic farmland were defined in the model, and the delineation goals and constraints have been formally expressed. The model introduced the immune system concepts to complement the existing theory. This paper describes the coding and initialization methods for the algorithm, particle position and speed update mechanism, and fitness function design. We selected Xun County, Henan Province, as the research area and set up control experiments that aligned with the different targets and compared the performance of the three models of particle swarm optimization (PSO), artificial immune algorithm (AIA), and the improved AIA-PSO in solving multi-objective problems. The experiments proved the feasibility of the model. It avoided the adverse effects of subjective factors and promoted the scientific rationality of the results of permanent basic farmland delineation.
Highlights
Over the past 60 years, the world has been undergoing rapid urbanization
It defines the general rules and objective function of permanent basic farmland delineation, as well as the formal representation of the constraints, and discusses the improvement of the particle swarm optimization (PSO) algorithm when combined with the artificial immune algorithm
Permanent basic farmland delineation was based on the local natural endowment and was combined with the area constraints, farming environment, and site conditions to optimize the selection of cultivated land units
Summary
Over the past 60 years, the world has been undergoing rapid urbanization. Since the 1960s, the more rapid the economic development and the accelerated urbanization process in a region was, the more serious the decline in cultivated land was in the region [1,2,3,4,5]. Artificial intelligence algorithms have had great advantages in solving multi-objective spatial planning problems and have been successfully applied in problems such as land resource allocation [28,29,30,31,32,33], spatial pattern optimization [34,35,36,37,38,39,40], space selection [41,42,43], and land use zoning [44,45,46,47]. It defines the general rules and objective function of permanent basic farmland delineation, as well as the formal representation of the constraints, and discusses the improvement of the PSO algorithm when combined with the artificial immune algorithm.
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