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SPIRE
2010
Springer
14 years 11 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
91
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GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
15 years 7 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 3 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...
100
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GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 6 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
132
Voted
PRL
2007
180views more  PRL 2007»
14 years 12 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...