Abstract
Land Use Cover and Change models are complex systems designed to simulate the effects of land use on a catchment area. This includes the profitability of different land use choices and their subsequent effect on the environment. In particular, some land use choices will increase salinity which in turn degrades the land, reducing crop yields and profitability in future years. The models are complex systems due to their size and the interdependence of their components. Computer-based models are useful in predicting the long term efects of land use. However, finding land use choices that match specific requirements can be difficult because of the large search space involved. This paper describes a genetic algorithm for finding solutions. The algorithm is implemented on a Beowulf cluster using Open MPI. Catchment data are distributed to nodes that simultaneously compute solutions using a genetic algorithm. These solutions are then collated by a central node.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IASK International Conference on E-Activity and Leading Technologies |
| Editors | M Munoz, A Freitas, P Cravo |
| Place of Publication | Portugal |
| Publisher | International Association for Scientific Knowledge (IASK) |
| Pages | 302-305 |
| ISBN (Print) | 9789729939754 |
| Publication status | Published - 31 Dec 2007 |
| Event | E-ALT 2007: IASK International Conference E-Activity and Leading Technologies 2007 - Porto, Portugal Duration: 3 Dec 2007 → 6 Dec 2007 |
Conference
| Conference | E-ALT 2007: IASK International Conference E-Activity and Leading Technologies 2007 |
|---|---|
| City | Porto, Portugal |
| Period | 3/12/07 → 6/12/07 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
Keywords
- Neural, Evolutionary and Fuzzy Computation
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