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GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
14 years 1 months ago
Automatic mutation test input data generation via ant colony
Fault-based testing is often advocated to overcome limitations of other testing approaches; however it is also recognized as being expensive. On the other hand, evolutionary algor...
Kamel Ayari, Salah Bouktif, Giuliano Antoniol
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
14 years 1 months ago
An informed convergence accelerator for evolutionary multiobjective optimiser
A novel optimisation accelerator deploying neural network predictions and objective space direct manipulation strategies is presented. The concept of directing the search through ...
Salem F. Adra, Ian Griffin, Peter J. Fleming
ANTSW
2008
Springer
13 years 9 months ago
Adaptive Particle Swarm Optimization
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...
Zhi-hui Zhan, Jun Zhang
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 11 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
BMCBI
2007
233views more  BMCBI 2007»
13 years 7 months ago
160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA)
Background: To infer homology and subsequently gene function, the Smith-Waterman (SW) algorithm is used to find the optimal local alignment between two sequences. When searching s...
Isaac T. S. Li, Warren Shum, Kevin Truong