基于小生境遗传算法的社区养老公共空间优化设计  

Optimization Design of Community Elderly Care Public Space Based on Niche Genetic Algorithm

作　　者：杨凡 刘珊 Yang Fan;Liu Shan(Yunnan Forestry Vocational and Technical College,Kunming 530100,Yunnan,China)

机构地区：[1]云南林业职业技术学院,云南昆明530100

出　　处：《绿色科技》2024年第5期45-50,共6页Journal of Green Science and Technology

摘　　要：常规的社区养老公共空间优化方法构建公共空间网络结构关联性较差,空间优化效果不佳。因此,基于小生境遗传算法,设计了一种社区养老公共空间优化方法。根据网络结构多元化、多层次和系统化的特点,构建社区养老公共空间网络结构,通过计算网络结构的关联性,判断当前网络结构的构建效果,在小生境遗传算法的作用下,通过计算网络结构节点的适应度,生成社区养老公共空间优化模型,从而输出切实有效的社区养老公共空间优化策略。通过上述的设计,完成对社区养老公共空间优化方法的设计。实验结果表明:与以往的社区养老公共空间优化方法相比,设计的基于小生境遗传算法的社区养老公共空间优化方法在实际应用中空间利用率高达97.82%,优化效果更好。The conventional optimization methods for community elderly care public space construction have poor correlation with the network structure of public space,and the spatial optimization effect is not satisfactory.Therefore,based on niche genetic algorithm,a community elderly care public space optimization method was designed.Based on the characteristics of diversified,multi-level,and systematic network structure,a community elderly care public space network structure is constructed.By calculating the correlation of the network structure,the current construction effect of the network structure is judged.Under the action of niche genetic algorithm,the fitness of network structure nodes is calculated to generate a community elderly care public space optimization model,thereby outputting practical and effective community elderly care public space optimization strategies.Through the above design,the design of optimization methods for community elderly care public spaces is completed.The experimental results show that compared with previous optimization methods for community elderly care public spaces,the designed community elderly care public space optimization method based on niche genetic algorithm has a space utilization rate of up to 97.82%in practical applications,and the optimization effect is better.

关 键 词：小生境遗传算法 社区养老 养老公共空间 优化方法 方法设计 

分 类 号：G642[文化科学—高等教育学]