Abstract
The inventorying of biological diversity and studies in biocomplexity require the management of large electronic datasets of organisms. While species inventory has adopted structured electronic databases for some time, the
computer modelling of the functional interactions between biological entities at all levels of life is still in the stage of development. One of the challenges for this type of modelling is the biotic interactions that occur between large datasets of entities represented as computer algorithms. In real-time simulation that models the biotic interactions of large population datasets, the use of computational processing time could be extensive. One way of increasing the efficiency of such simulation is to partition the landscape so that entities need only traverse its local space for entities that falls within the interaction proximity. This article presents an efficient segmentation algorithm for biotic
interactions for research related to the modelling and simulation of biological systems.
computer modelling of the functional interactions between biological entities at all levels of life is still in the stage of development. One of the challenges for this type of modelling is the biotic interactions that occur between large datasets of entities represented as computer algorithms. In real-time simulation that models the biotic interactions of large population datasets, the use of computational processing time could be extensive. One way of increasing the efficiency of such simulation is to partition the landscape so that entities need only traverse its local space for entities that falls within the interaction proximity. This article presents an efficient segmentation algorithm for biotic
interactions for research related to the modelling and simulation of biological systems.
| Original language | English |
|---|---|
| Article number | 6(1) |
| Pages (from-to) | 5-17 |
| Number of pages | 12 |
| Journal | Biodiversity Informatics |
| Volume | 6 |
| Issue number | 1 |
| Publication status | Published - 2009 |
Keywords
- segmentation, optimisation algorithms, artificial life, individual-based model, agent-based model, entity interaction