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» Data Mining for Genetics: A Genetic Algorithm Approach
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GECCO
2003
Springer
123views Optimization» more  GECCO 2003»
14 years 2 months ago
Benefits of Implicit Redundant Genetic Algorithms for Structural Damage Detection in Noisy Environments
A robust structural damage detection method that can handle noisy frequency response function information is discussed. The inherent unstructured nature of damage detection problem...
Anne M. Raich, Tamás Liszkai
PPSN
1998
Springer
14 years 1 months ago
Restart Scheduling for Genetic Algorithms
Abstract. In order to escape from local optima, it is standard practice to periodically restart a genetic algorithm according to some restart criteria/policy. This paper addresses ...
Alex S. Fukunaga
TEC
2008
97views more  TEC 2008»
13 years 9 months ago
Ergonomic Chair Design by Fusing Qualitative and Quantitative Criteria Using Interactive Genetic Algorithms
This paper emphasizes the necessity of formally bringing qualitative and quantitative criteria of ergonomic design together, and provides a novel complementary design framework wit...
Alexandra Melike Brintrup, Jeremy Ramsden, Hideyuk...
CEC
2007
IEEE
14 years 3 months ago
A genetic algorithm for solving the binning problem in networked applications detection
Network administrators need a tool that detects the kind of applications running on their networks, in order to allocate resources and enforce security policies. Previous work sho...
Maxim Shevertalov, Edward Stehle, Spiros Mancoridi...
ICTAI
2007
IEEE
14 years 3 months ago
A Java-Based Distributed Genetic Algorithm Framework
Distributed Genetic Algorithm (DGA) is one of the most promising choices among the optimization methods. In this paper we describe DGAFrame, a flexible framework for evolutionary...
Gabi Escuela, Yudith Cardinale, Jorge Gonzá...