Relative Eco-Efficiency Recognition Based on DEA Neural Network

Abstract

Regional eco-efficiency is regarded as a relative concept. It could be presented the relative eco-efficiency with the change of economy and environment. That means it could not the optimal compared with the predicted optimum in the future. It would be a basis of policy decision making of local governments according to identify the life cycle stage of current regional eco-efficiency. As a beneficial supplement of the eco-efficiency measurement, this paper set up a DEA Neural Network recognition model which can effectively analyze and identify the current relative eco-efficiency of a regional. The empirical research shows that the phenomenon of forecasted value “floating upon” has been restrained effectively. It is an obvious advantage that this method is showed as a method of fast convergence, accurate identification, extensive application and promotion value in practice.