Research Article
An Ant Colony Biological Inspired Way For Statistical Shortest Paths In Complex Brain Networks
@INPROCEEDINGS{10.4108/icst.bodynets.2012.249961, author={Fei GAO and Feng-xia Fei and Ilangko Balasingham}, title={An Ant Colony Biological Inspired Way For Statistical Shortest Paths In Complex Brain Networks}, proceedings={7th International Conference on Body Area Networks}, publisher={ICST}, proceedings_a={BODYNETS}, year={2012}, month={11}, keywords={ant colony optimization; brain networks; biology inspired methods; statistical shortest path}, doi={10.4108/icst.bodynets.2012.249961} }- Fei GAO
Feng-xia Fei
Ilangko Balasingham
Year: 2012
An Ant Colony Biological Inspired Way For Statistical Shortest Paths In Complex Brain Networks
BODYNETS
ICST
DOI: 10.4108/icst.bodynets.2012.249961
Abstract
What is the mechanism of information transferring, when some of the brain nerves' links do not work? Brain is the most complex, ingenious processing system in world. The complex brain networks is an inter-discipline of complex networks and neuroscience. In this paper, an ant colony optimizations are introduced to solve the crux, shortest path for information transferring mechanism. Some reviews are presented on progress of complex brain networks and computational neuroscience firstly. The deep research on brain complex networks will have a profound effects on artificial intelligence methods which models the mechanisms. Then simulations are done to finding shortest path in probabilities for theoretical nerve networks through ant colony optimization methods. The results show the proposed way is a successful method in detecting the statistical shortest path in brain networks when nerves' link broken, with the advantages of fast convergence and robustness.