Overview of UrbanSim and the Open Platform for Urban Simulation

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Data ImputationK-Nearest Neighbors for Continuous AttributesAttributes: Stories, Bldg SF,Improvement Value, etc."KNN Basics:"Finds k closest neighbors in ndimensional space."Uses k neighbors target valuesto make prediction."
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Page 2 and 3: Agenda• UrbanSim Overview• Simp
Page 4 and 5: UrbanSim ObjectivesMust assess the
Page 6 and 7: UrbanSim Models:Über-Über-Simplif
Page 8 and 9: UrbanSim Models: Zonal VersionHouse
Page 10 and 11: Model Specification: Multinomial Lo
Page 12 and 13: Employment Location ChoicePredicts
Page 14 and 15: Model Assessment Methods• Assessm
Page 16 and 17: Historical Validation from 1980 - 1
Page 18 and 19: Comparison of Predicted to Observed
Page 20 and 21: Design Requirements for Opus• Ope
Page 23 and 24: Integrated Estimation & Application
Page 25 and 26: Integration of HeterogeneousCompone
Page 27 and 28: Data Integration in UrbanSim27
Page 29 and 30: New Model System Based onParcels an
Page 31 and 32: Input Data: UGB and Environmental
Page 33 and 34: Input Data: Employment
Page 35 and 36: The Magnitude of the ProblemSeattle
Page 37: Data Imputation Tool
Page 42 and 43: Machine Learning/Data MiningSo far,
Page 44: Results: Completion and ValidationR

Overview of UrbanSim and the Open Platform for Urban Simulation

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