RESEARCH ON OPTIMIZATION OF LAND ALLOCATION BASED ON A PARTICLE SWARM OPTIMIZATION ALGORITHM IN URBAN AND RURAL PLANNING

ABSTRACT Rational planning and layout of land types in urban and rural areas can realize the rational use of resources. This paper briefly introduces the optimization model of land allocation for urban and rural planning and uses a particle swarm optimization (PSO) algorithm to solve the land allocation scheme. At the same time, co-evolution was introduced into the PSO algorithm to improve its optimization performance. Then, Chongqing city was taken as an example to optimize the land allocation scheme. The results showed that the three algorithms optimized the land allocation scheme, and the improved PSO algorithm had the best optimization effect. In conclusion, the PSO algorithm optimized by the co-evolution concept can effectively optimize land allocation schemes.

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Publication Details

Journal
Journal of Green Building
Published
2025-01-01
DOI
https://doi.org/10.3992/jgb.20.3.215
Primary Topic
Remote Sensing and Land Use
Type
article
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article

RESEARCH ON OPTIMIZATION OF LAND ALLOCATION BASED ON A PARTICLE SWARM OPTIMIZATION ALGORITHM IN URBAN AND RURAL PLANNING

Wanting He, Hai Huang
Journal of Green Building
Remote Sensing and Land Use
article

RESEARCH ON OPTIMIZATION OF LAND ALLOCATION BASED ON A PARTICLE SWARM OPTIMIZATION ALGORITHM IN URBAN AND RURAL PLANNING

Wanting He, Hai Huang
article en

Abstract

ABSTRACT Rational planning and layout of land types in urban and rural areas can realize the rational use of resources. This paper briefly introduces the optimization model of land allocation for urban and rural planning and uses a particle swarm optimization (PSO) algorithm to solve the land allocation scheme. At the same time, co-evolution was introduced into the PSO algorithm to improve its optimization performance. Then, Chongqing city was taken as an example to optimize the land allocation scheme. The results showed that the three algorithms optimized the land allocation scheme, and the improved PSO algorithm had the best optimization effect. In conclusion, the PSO algorithm optimized by the co-evolution concept can effectively optimize land allocation schemes.

Journal of Green BuildingVol. 20(3)
Zhejiang Industry Polytechnic College (CN), Chongqing Vocational Institute of Engineering (CN)
Openalex Percentile: Top 69%
Remote Sensing and Land Use
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