<p>A landscape intelligent design system based on a particle swarm optimization algorithm and polygon layout is proposed. The system focuses on urban parks as the primary research object, and combines knowledge graphs and heuristic layout algorithms to optimize the landscape design process. The performance test results showed that the particle swarm algorithm had the fastest convergence speed, completing convergence within 12.62&#xa0;min. However, in terms of average convergence value, the performance of the particle swarm optimization algorithm was relatively low, with an average convergence value of 0.9723. The comparison results before and after completing the design case showed that the designed plant community structure was relatively continuous without obvious faults, resulting in a concentrated distribution for shrubs. The landscape intelligent design system has a good user experience, which can meet the design requirements.</p>

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An AI-driven urban landscape planning decision support system using PSO and knowledge graphs

  • Yu Kang

摘要

A landscape intelligent design system based on a particle swarm optimization algorithm and polygon layout is proposed. The system focuses on urban parks as the primary research object, and combines knowledge graphs and heuristic layout algorithms to optimize the landscape design process. The performance test results showed that the particle swarm algorithm had the fastest convergence speed, completing convergence within 12.62 min. However, in terms of average convergence value, the performance of the particle swarm optimization algorithm was relatively low, with an average convergence value of 0.9723. The comparison results before and after completing the design case showed that the designed plant community structure was relatively continuous without obvious faults, resulting in a concentrated distribution for shrubs. The landscape intelligent design system has a good user experience, which can meet the design requirements.