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基于多目标规划模型的轨道交通周边土地优化研究

Study on Land Optimization Around Rail Transit Based on Multi-objective Planning Model
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摘要 土地是否合理使用关系到城市空间布局的合理性,直接影响城市是否能够快速健康地发展。为优化轨道交通站点研究范围内的土地布局,本文提供一种基于多目标规划函数的定量研究方法,以保障客流量、保证民生质量及开发合理化作为影响土地优化为目标,对模型参数提前假设,选取西宁地铁一号线博文路站作为研究对象。通过调查,发现研究区域内存在就业机会少、周边居民配套设施不足等问题,将模型应用于研究对象,利用Matlab计算得到研究区域内土地优化后的方案。运算结果表明,新方案能够提高商业用地与基础设施用地占比,并给出具体的占比量值,对于轨道交通站点周边的土地优化具有可操作性。 The rational use of land is related to the rationality of urban spatial layout and directly affects the rapid and healthy development of the city.In order to optimize the land layout within the research scope of rail transit stations,this paper provides a quantitative research method based on multi-objective planning function,selects three major objectives that affect the land optimization,namely guarantee of passenger flow,good quality of people s livelihood and rationalization of development,and assumes the model parameters in advance.On this basis,Bowen Road Station of Xining Metro Line 1 is selected as the research object.Through the investigation,it is found that there are few employment opportunities in the current study area and the lack of supporting facilities for the residents.Applying models to research objects,the optimized scheme of land in the study area is obtained by Matlab calculation.The calculation results show that the new scheme can improve the proportion of commercial land and infrastructure land,and give the specific value of the proportion,which is feasible to optimize the land around the rail transit station.
作者 魏薇 张利 余丽洁 WEI Wei;ZHANG Li;YU Lijie(Shaanxi Polytechnic Institute,Xianyang 712000,Shaanxi,China;Xi Xian New Area Rail Transit Investment and Construction Co.,Ltd,Xi an 710116,Shaanxi,China;School of Transportation Engineering,Chang an University,Xi an 710064,Shaanxi,China)
出处 《广东交通职业技术学院学报》 2024年第1期41-44,54,共5页 Journal of Guangdong Communication Polytechnic
基金 陕西省自然科学基金:城市轨道交通客流与土地利用时空协同研究(编号:2022JQ-455)。
关键词 土地优化 轨道交通 多目标规划模型 西宁市 land optimization rail transit multi-objective planning model Xining City
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