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نماذج التفاعل المكاني (الجاذبية)×تحليل القرار متعدد المعايير المستند إلى نظم المعلومات الجغرافية (GIS-MCDA)×الانحدار اللوجستي متعدد الحدود×
المجالالتحليل المكانيالتحليل المكانيالاقتصاد القياسي
العائلةRegression modelProcess / pipelineRegression model
سنة النشأة197120061974
صاحب الطريقةAlan Wilson (entropy-maximizing family)Jacek Malczewski (GIS-MCDA synthesis)McFadden
النوعModel of flows between spatial origins and destinationsSpatial multi-criteria suitability/decision analysisMultinomial logistic regression
المصدر التأسيسيWilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726. DOI ↗McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503
الأسماء البديلةgravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeliGIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitabilitymultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
ذات صلة445
الملخصSpatial 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.GIS-MCDA combines the map layers of a geographic information system with multi-criteria decision analysis to produce suitability or priority maps — ranking locations by how well they satisfy several weighted criteria at once. It is the standard framework for spatial decisions such as siting hospitals, solar farms, landfills, or evacuation areas, integrating methods like AHP, TOPSIS, and weighted overlay with spatial data.Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category.
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ScholarGateقارن الطرق: Spatial Interaction Model · GIS-MCDA · Multinomial Logit. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare