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| 1 | 基于GAN的城市快递自提服务设施选址优化研究显示文摘快递自提点作为社区服务设施,其选址落位影响着城市居民的生活便利程度,目前已经成为不可或缺的服务设施类型.爬取城市快递自提点POI数据、城市人口密度数据与百度地图城市空间形态影像数据,将矢量化处理后的道路数据通过sDNA计算道路接近度与穿行度两种空间参数,并运用ArcGIS平台将POI数据生成点密度热力图,通过渔网工具划分城市单元,对人口密度数据、道路网络结构测度数据、自提点密度数据进行矢量化重分类处理.计算城市空间形态、人口密度、道路网络测度与自提点的相关性,并以此建立天津社区生活圈自提点与城市空间数据集.探索自提点的选址规律,建立深度学习GAN模型.再通过计算Pix2PixHD算法训练过程的生成器与判别器的损失值来验证模型可行性.并使用成都城市空间数据集进行测试以检验模型准确性,最后引入SVM、随机森林、线性回归模型进行准确性对比,结果显示GAN模型具有较高的预测准确度(余弦相似度0.89,dHash相似度0.78,SSIM相似度0.70).通过人口密度和城市空间形态参数的GAN深度学习模型成功预测了自提点热图,验证了机器学习基于经验与量化技术的决策能力.以寻求一种基于人工智能的城市社区生活圈快递服务设施布局的生成方法,为未来社区服务设施选址提供了新思路. | 胡一可 温雯 刘雅心 郑豪 | 2022 | 天津大学学报(自然科学与工程技术版)2022，55，12： | 0 |
| 2 | Identifying the Geography and Determinants of O2O Online Retailers in Megacity in Central China:A Case Study of Zhengzhou City显示文摘In recent years,O2O e-commerce,represented by online group-buying,has developed vigorously,which had significant impacts on urban commercial space.Zhengzhou City is a rising national central city in China,and its e-commerce development level is ahead,but relevant researches are rare.Therefore,the data of online retailers of Meituan.com was collected and combined with Baidu map and Baidu heat map data.Then,we adopted the methods such as spatial statistics and geodetector to explore the geography and determinants of O2O online retailers in Zhengzhou urban area.The main conclusions are 1)The spatial development of O2O online retailers is characterized by significant global high-value agglomeration.2)The agglomeration areas of different types of O2O online retailers are different.Most of them are concentrated in the old urban area within the Third Ring Road of Zhengzhou City,forming five comprehensive agglomeration areas.3)The areas with the high e-commerce development level are mainly concentrated in the northeast and southwest of the x-shaped region formed by the intersection of Lianyungang-Lanzhou and Beijing-Guangzhou railways.Erqi Square and Guomao 360 Plaza are at the highest development level,followed by Zhongyuan Wanda Plaza and Daxue Middle Road.The development level at other areas is relatively low.4)Zhengzhou’s O2O commercial pattern is highly dependent on physical business.The population distribution,especially the population distribution during the nightlife period,plays a vital role in its spatial development,followed by accessibility.The influences of physical distance are slightly larger than that of time cost,but the difference between them is little.In addition,travelling costs have the least impact.This paper could provide certain references for urban commercial planning. | QI Jinghui NIU Shuwen YE Chenxi WANG Luojia WEl Yongna WEN Yuzhao ZHAO Shuling | 2021 | Chinese Geographical Science2021，31，5： | 0 |
| 3 | 基于POI数据的城市物流末端节点空间布局及影响因素研究——以上海市为例显示文摘随着电商物流配送业务量越来越大,城市物流末端节点数量不断增加,推动其末端体系建设逐渐成为民生关注的一个重点问题。结合节点所属企业的属性和POI数量,将上海市物流末端节点分为大型、中型和小型规模节点三个类型。利用ARCGIS软件,采用标准差椭圆、核密度分析、相关性检验和缓冲区分析的方法,对上海市物流末端节点的空间布局及影响因素进行分析。结果表明:上海市物流末端节点的空间分布范围广,整体上从市中心向郊区不断蔓延扩散,集聚模式又呈现“双核多中心”的发展趋势;由于企业资源禀赋和所在区域环境的差异,小型规模节点的分布方向和范围具有不同的特点;交通便利性和政策因素对各类型物流末端节点的分布有着很大的影响,大型、中型规模节点的分布与各区的人口密度、经济发展水平联系紧密,而小型规模节点的相关性则不明显;末端节点的布局策略和规模大小反映了不同经营单位的发展阶段和战略决策。 | 杨鹏 龙小凤 肖玲 王雨欣 王礼霞 | 2023 | 湖南人文科技学院学报2023，40，5： | 0 |
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