Identification method of residents' medical travel behavior characteristics driven by mobile signaling data: A Case Study of Kunshan

Abstract

With quick development of big data technology, how to analyze the characteristics of residents' medical travel behavior comprehensively and accurately provides basic data support for the supply and demand evaluation of urban public medical service facilities and the layout optimization decision-making. Aiming at the limitations of traditional traffic data sources, a method for identifying urban residents' medical travel behavior characteristics using mobile phone signaling data under the LTE network as the core data source was constructed. Taking Kunshan City as an example, this method identifies the characteristics of users' stay behavior, workplace and residence, and travel OD information based mobile signaling data. Then this method combines the POI data of medical public service facilities, and obtains the corresponding relationship table between hospital and mobile base station through the association matching between mobile base station and grade hospital. Finally, the method identifies the OD of medical travel behavior based on the information, which include travel OD and characteristics of residents' workplace and residence and stay behavior obtained from signaling data, and the corresponding relationship between hospital and mobile base station, and comprehensively analyzes the individual attribute characteristics and travel characteristics of urban residents who have had medical travel behavior.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 2 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.