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Багатокритеріальний аналіз рішень на основі ГІС (GIS-MCDA)×Моделі розміщення-розподілу×Мультиноміальна логістична регресія×
ГалузьПросторовий аналізПросторовий аналізЕконометрика
РодинаProcess / pipelineProcess / pipelineRegression model
Рік появи200619631974
Автор методуJacek Malczewski (GIS-MCDA synthesis)Leon Cooper; S. L. HakimiMcFadden
ТипSpatial multi-criteria suitability/decision analysisSpatial facility-location optimizationMultinomial logistic regression
Основоположне джерелоMalczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726. DOI ↗Cooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343. 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
Інші назвиGIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitabilityfacility location, p-median problem, maximal covering location problem, yer-tahsis modellerimultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
Пов'язані445
ПідсумокGIS-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.Location-allocation models decide where to place a set of facilities and simultaneously assign demand points to them so as to optimize an objective such as total travel cost, worst-case distance, or population covered. Rooted in the operations-research work of Cooper (1963) and Hakimi (1964) and central to network GIS, they answer questions like where to site warehouses, hospitals, fire stations, or schools to best serve a spatially distributed population.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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ScholarGateПорівняння методів: GIS-MCDA · Location-Allocation · Multinomial Logit. Отримано 2026-06-17 з https://scholargate.app/uk/compare