基于集群智能行为模拟与空间句法分析的城市公园优化设计研究

行为模拟是对城市公园规划设计方案未来实际使用情况的预期和研判,也是辅助方案优化调整的关键步骤。采用集群智能方法及其微粒群算法,从微观视角模拟使用人群的漫游行为,并随着模拟过程的推进观察使用者的动态活动轨迹与分布特征,及时发现设计方案中存在的问题。在此基础上,进一步利用空间句法分析,通过调整局部道路结构,改变待优化区域与邻近人流密集区域之间拓扑深度的方式,实现方案优化设计,从而形成自下而上行为模拟与自上而下空间分析相结合的方案优化思路。以期为提高城市公园利用效率、建设优质的景观空间提供新思路。

Research on Optimization of Urban Park DesignBased on Swarm Intelligent Simulation and SpatialSyntax Analysis

Behavior simulation is not only the expectation andjudgment of the future practical use of the urban green parkplanning and design scheme, but also the key content of theoptimization and adjustment of the scheme design. Through thecluster intelligence method and its particle swarm optimizationalgorithm, the roaming behavior of users is simulated from a microperspective, and with the advancement of the simulation process,the activity track is observed to find some forgotten landscape areasin the planning scheme. On this basis, through further use of spacesyntax, the optimal design is achieved by adjusting the local roadstructure, and changing the topological depth between the area tobe optimized and the adjacent densely populated areas. Thus, theoptimization idea is developed by combining bottom-up behaviorsimulation and top-down spatial analysis, which aims to provide anew idea to improve the utilization efficiency of urban parks, andbuild high-quality landscape space.