  We introduce a predictive algorithm for the smart growth of cities with
populations upward of 100,000, allowing for extensive simulations of growth
plans and their effects upon an urban populous. A smart growth metric is
calculated to evaluate the progress of a city at each phase of its adaptation
of the growth plan, which is measured using a weighted entropy method. The
predictive algorithm itself is built from a unique differential model, which
calculates the growth of a city from smart growth proposals that are
individually assessed by a logistic weight model. These proposals are then
sorted based on effectiveness and efficiency observed from the simulations,
giving insight into the best approach to providing the target cities with a
hopeful future.
