A Multi-Objective Permanent Basic Farmland Delineation Model Based on Hybrid Particle Swarm Optimization
| Autor: | Ke Nie, Wei Huang, Hua Wang, Wenwen Li |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Optimization problem 010504 meteorology & atmospheric sciences Computer science Geography Planning and Development 0211 other engineering and technologies Initialization lcsh:G1-922 02 engineering and technology Artificial immune algorithm 01 natural sciences multi-objective artificial immune algorithm Earth and Planetary Sciences (miscellaneous) permanent basic farmland Computers in Earth Sciences 0105 earth and related environmental sciences Fitness function particle swarm optimization Particle swarm optimization 021107 urban & regional planning spatial optimization Particle position Cultivated land Xun County lcsh:Geography (General) Coding (social sciences) |
| Zdroj: | ISPRS International Journal of Geo-Information Volume 9 Issue 4 ISPRS International Journal of Geo-Information, Vol 9, Iss 243, p 243 (2020) |
| ISSN: | 2220-9964 |
| DOI: | 10.3390/ijgi9040243 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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