Neural networks for managing multifamily properties

This research used neural networks to develop a decision support system, and model the relationship between one´s living environment and residential satisfaction. Residential satisfaction was investigated at two affordable housing multifamily rental properties located in Atlanta, Georgia. The neural network was trained using data from Defoors Ferry Manor and the network was validated using data from Moores Mill. The neural network accurately categorized ninety-eight percent of the cases in the training set and ninety-three percent of the cases in the validation test set. This research represents a first attempt to use neural networking to model the relationship between one´s living environment and residential satisfaction