%0 Journal Article
%T 基于不动产统一登记数据的个体迁居行为算法<br>Individual Migration Behavior Algorithm Based on Unified Real Estate Registration Data
%A 梁帅
%A 辜寄蓉
%A 符卓
%A 姚敏
%A 方从刚
%A 张其海
%A 李晓铃
%A 刘光辉
%J Geographical Science Research
%P 86-98
%@ 2168-5770
%D 2022
%I Hans Publishing
%R 10.12677/GSER.2022.111010
%X 在城市地区，居民迁居反映了人们与社会或物理环境的互动。不动产统一登记数据是完整存储了权利人、房屋坐落和宗地信息的数据，权利人的房屋购买行为，是个体迁居意愿的表达。研究以不动产统一登记数据为基础，按权利人购房行为的时间，生成套次数据。套次与套次之间建立个体迁居轨迹，通过对聚类算法的改进，在空间密度算法的基础上，对迁居轨迹进行了相似性度量，较好地解决了轨迹聚类问题，对成都市的个体迁居行为进行了提炼和分析。结果显示了套次与套次之间迁居行为的差异，较好地挖掘出迁居行为的时空特征，为房地产市场监管提供了新的思路。<br />
In urban areas, residents’ migration reflects the interaction between social or physical environment. The unified real estate registration data completely store the information of each obligee, the location of the house and the parcel. The house purchase behavior of the obligee is the expression of the individual’s willingness to move. Based on the unified real estate registration data, this paper generates the set data according to the time of the obligee’s purchase behavior. Through the improvement of the clustering algorithm, based on the spatial density algorithm, this paper measures the similarity of the migration trajectory, solves the problem of trajectory clustering, and refines and analyzes the individual migration behavior in Chengdu. The results show the differences in the migration behavior between the set times, and better excavate the temporal and spatial characteristics of the migration behavior, which provides a new idea for the real estate market supervision.
%K 个体迁居行为算法，空间聚类算法，空间密度算法，时空特征，不动产统一登记数据<br>Individual Migration Behavior Algorithm
%K Spatial Clustering Algorithm
%K Spatial Density Algorithm
%K Spatial and Temporal Characteristics
%K Unified Real Estate Registration Data
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=48598