Ecological Footprint forecasting and estimating using neural networks and DEA
by Dexiang Wu, Liang Liang
International Journal of Global Environmental Issues (IJGENVI), Vol. 9, No. 3, 2009

Abstract: 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.

Online publication date: Thu, 09-Jul-2009

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