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» Evolving Complex Neural Networks
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EOR
2006
88views more  EOR 2006»
14 years 10 months ago
Nonessential objectives within network approaches for MCDM
In Gal and Hanne [Eur. J. Oper. Res. 119 (1999) 373] the problem of using several methods to solve a multiple criteria decision making (MCDM) problem with linear objective functio...
Tomas Gal, Thomas Hanne
71
Voted
MSWIM
2005
ACM
15 years 3 months ago
YAES: a modular simulator for mobile networks
Developing network protocols for mobile wireless systems is a complex task, and most of the existing simulator frameworks are not well suited for experimental development. The YAE...
Ladislau Bölöni, Damla Turgut
INFOCOM
2008
IEEE
15 years 4 months ago
Modeling the Evolution of Degree Correlation in Scale-Free Topology Generators
—In this paper, we examine the asymptotic behavior of degree correlation (i.e., the joint degree distribution of adjacent nodes) in several scale-free topology generators GED [13...
Xiaoming Wang, Xiliang Liu, Dmitri Loguinov
72
Voted
GECCO
2009
Springer
15 years 2 months ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz
74
Voted
BILDMED
2006
120views Algorithms» more  BILDMED 2006»
14 years 11 months ago
Towards Automatic Segmentation of Serial High-Resolution Images
Developing barley grains are to be visualised by a 4-D model, in which spatiotemporal experimental data can be integrated. The most crucial task lies in the automation of the exten...
Cornelia Brüß, Marc Strickert, Udo Seif...