Ecological footprint forecasting and estimating using neural networks and DEA

There is a growing consensus that social and economic sustainability depends on limited natural capital. Ecological Footprint (EF) provides an alternative tool to account for natural capital. This study presents two models to research Wuhan's natural capital: first using Genetic Algorithm Neural Networks (GANN) model to forecast the EF; second, employing the DEA model to estimate the ecosystem effectiveness across different years. Case study is conducted for a big Chinese city where favourable computation is yielded.