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SPIRE
2010
Springer
15 years 1 months ago
Why Large Closest String Instances Are Easy to Solve in Practice
We initiate the study of the smoothed complexity of the Closest String problem by proposing a semi-random model of Hamming distance. We restrict interest to the optimization versio...
Christina Boucher, Kathleen Wilkie
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
15 years 9 months ago
Neural network ensembles for time series forecasting
This work provides an analysis of using the evolutionary algorithm EPNet to create ensembles of artificial neural networks to solve a range of forecasting tasks. Several previous...
Victor M. Landassuri-Moreno, John A. Bullinaria
JNCA
2011
102views more  JNCA 2011»
14 years 5 months ago
Multi-objective zone mapping in large-scale distributed virtual environments
In large-scale distributed virtual environments (DVEs), the NP-hard zone mapping problem concerns how to assign distinct zones of the virtual world to a number of distributed serv...
Ta Nguyen Binh Duong, Suiping Zhou, Wentong Cai, X...
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 8 months ago
Evolutionary testing of state-based programs
The application of Evolutionary Algorithms to structural test data generation, known as Evolutionary Testing, has to date largely focused on programs with input-output behavior. H...
Phil McMinn, Mike Holcombe
PRL
2007
180views more  PRL 2007»
15 years 2 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...