An evaluating model for smart growth plan based on BP neural network and set pair analysis

Abstract

Smart growth, as a service to the economy, environment and society, has increasingly become the development pattern for cities of the world, but the degree of smart growth varies from city to city, and not all smart growth plans are suitable for current cities or countries. Therefore, it is of practical significance to measure the success degree of smart growth plan. The current model is accompanied by some problems such as subjectivity, unable to prioritize each plan, and so on. In this paper, an evaluating model was established to scientifically measure and adjust the smart growth plan based on BP neural network and set pair analysis. In this model, an evaluating metric(I) was defined, which was obtained by multiplying the ability score(A) and the coordinative development index(C). Applied to city's current plan, the model can tell us how successful the current plan is for this city, thus on the basis of evaluating result, better new plans for the city in the future can be developed. Finally, the effects of the new plans for population, economy-environment- society were discussed based on Lokta-Volterra equations and the environmental Kuznets curve. A case study was presented in two cities, Karamay and Atlanta. The result showed that the current plan in Atlanta is more successful than that in Karamay, but both the two plans are moderately successful. According to the results, a series of new plans were proposed and their priorities were ranked, the result showed that Atlanta should give priority to urban greening while Karamay give priority to economic development, and the effect of the scientific intelligence growth plan is to expand city's environmental capacity, promote the fair competition between the foreign population and the local population, and improve the balanced node, making the environment damage smaller, society and economic grow better. The model provides powerful reference for cities in developed and developing countries to formulate smart growth plans, especially for developing countries.