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» A hybrid approach to parameter tuning in genetic algorithms
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WCE
2007
13 years 8 months ago
Optimizing Designs based on Risk Approach
— In this paper a new approach to optimize nuclear power plant designs based on global risk reduction are described. In design the focus is on as components quality as redundancy...
Jorge E. Núñez Mc Leod, Selva S. Riv...
GECCO
2006
Springer
143views Optimization» more  GECCO 2006»
13 years 11 months ago
Hybrid search for cardinality constrained portfolio optimization
In this paper, we describe how a genetic algorithm approach added to a simulated annealing (SA) process offers a better alternative to find the mean variance frontier in the portf...
Miguel A. Gomez, Carmen X. Flores, Maria A. Osorio
IROS
2007
IEEE
171views Robotics» more  IROS 2007»
14 years 1 months ago
A Kalman filter for robust outlier detection
— In this paper, we introduce a modified Kalman filter that can perform robust, real-time outlier detection in the observations, without the need for parameter tuning. Robotic ...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
ECML
2007
Springer
14 years 1 months ago
Learning an Outlier-Robust Kalman Filter
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quali...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
GECCO
2004
Springer
14 years 1 months ago
Systematic Integration of Parameterized Local Search Techniques in Evolutionary Algorithms
Application-specific, parameterized local search algorithms (PLSAs), in which optimization accuracy can be traded off with runtime, arise naturally in many optimization contexts....
Neal K. Bambha, Shuvra S. Bhattacharyya, Jürg...