325 search results - page 22 / 65 » Evolvable network architectures: what can we learn from biol... |
HOTOS
1999
IEEE
14 years 27 days ago
1999
IEEE
In this position paper we motivate and describe the Congestion Manager (CM), a novel end-system architecture, which enables application adaptation to network congestion. The CM ma...
Publication
A large class of systems of biological and technological relevance can be described as analog networks, that is, collections of dynamic devices interconnected by links of varying s...
TGIS
2002
13 years 8 months ago
2002
Traditional GISystems are no longer appropriate for modern distributed, heterogeneous network environments due to their closed architecture, and their lack of interoperability, reu...
APIN
2010
13 years 8 months ago
2010
Artificial neural networks can be trained to perform excellently in many application areas. While they can learn from raw data to solve sophisticated recognition and analysis prob...
GECCO
2007
Springer
14 years 2 months ago
2007
Springer
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....