ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

코호트-컴포넌트 인구 추계×이동 및 이주에 대한 방사선 모델×공간 상호작용 (중력) 모형×
분야인구학공간분석공간분석
계열Process / pipelineRegression modelRegression model
기원 연도200120121971
창시자Preston, Heuveline & GuillotFilippo Simini et al.Alan Wilson (entropy-maximizing family)
유형Demographic projection pipelineParameter-free spatial interaction modelModel of flows between spatial origins and destinations
원전Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2Simini, F., González, M. C., Maritan, A., & Barabási, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100. DOI ↗Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗
별칭Cohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen ProjeksiyonuRadiation Law of Human Mobility, Parameter-free Mobility Model, Simini Radiation Model, Radyasyon Modeligravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
관련334
요약Cohort-Component Projection is the standard demographic method for forecasting future population size and age-sex structure by explicitly tracking births, deaths, and migration for each age-sex cohort across discrete time steps. Systematically formalized in the textbook literature by Preston, Heuveline, and Guillot (2001), the method builds on foundational actuarial and demographic work dating to the early twentieth century and remains the workhorse technique used by national statistical offices and international organizations worldwide.The Radiation Model, introduced by Simini et al. in 2012, is a parameter-free model for predicting human mobility and migration flows between geographic locations. Drawing an analogy from radiation physics, it predicts trip volumes based solely on population sizes at origin and destination, and the intervening population within the circle connecting them. It has been widely applied to commuting flows, migration, and epidemic spreading.Spatial interaction models predict the volume of flows — migrants, commuters, shoppers, trade, trips — between origins and destinations as a function of the size of each place and the distance or cost separating them. By analogy to Newton's gravity, interaction rises with the 'mass' of origin and destination and falls with separation, and Wilson's 1971 entropy-maximizing family put these models on a rigorous footing for transport, migration, and retail analysis.
ScholarGate데이터셋
  1. v1
  2. 1 출처
  3. PUBLISHED
  1. v1
  2. 1 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: Cohort-Component Projection · Radiation Model · Spatial Interaction Model. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare