Title: Ecological Footprint forecasting and estimating using neural networks and DEA

Authors: Dexiang Wu, Liang Liang

Addresses: School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei Anhui 230026, China. ' School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei Anhui 230026, China

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.

Keywords: ecological footprint; evaluation; DEA; data envelopment analysis; forecasting; sustainability; sustainable development; China; natural capital; genetic algorithms; neural networks; ecosystems.

DOI: 10.1504/IJGENVI.2009.026946

International Journal of Global Environmental Issues, 2009 Vol.9 No.3, pp.249 - 258

Published online: 09 Jul 2009 *

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