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.
| Original language | English |
|---|---|
| Pages (from-to) | 249-258 |
| Number of pages | 10 |
| Journal | International Journal of Global Environmental Issues |
| Volume | 9 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 2009 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- DEA
- Data envelopment analysis
- EF
- Ecological footprint
- Evaluation
- Neural networks
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