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GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 9 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
15 years 7 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
EUROGP
2009
Springer
143views Optimization» more  EUROGP 2009»
15 years 4 months ago
A Real-Time Evolutionary Object Recognition System
We have created a real-time evolutionary object recognition system. Genetic Programming is used to automatically search the space of possible computer vision programs guided throug...
Marc Ebner
GECCO
2010
Springer
207views Optimization» more  GECCO 2010»
15 years 11 months ago
Generalized crowding for genetic algorithms
Crowding is a technique used in genetic algorithms to preserve diversity in the population and to prevent premature convergence to local optima. It consists of pairing each offsp...
Severino F. Galán, Ole J. Mengshoel
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
15 years 7 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...