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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 8 months ago
A parallel evolutionary algorithm for unconstrained binary quadratic problems
In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master...
István Borgulya
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
13 years 8 months ago
Combatting financial fraud: a coevolutionary anomaly detection approach
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Shelly Xiaonan Wu, Wolfgang Banzhaf
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving computer intrusion scripts for vulnerability assessment and log analysis
Evolutionary computation is used to construct undetectable computer attack scripts. Using a simulated operating system, we show that scripts can be evolved to cover their tracks a...
Julien Budynek, Eric Bonabeau, Ben Shargel
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer