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» Exploring a Two-Population Genetic Algorithm
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GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
13 years 8 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
CEC
2008
IEEE
14 years 1 months ago
A contour method in population-based stochastic algorithms
—Inspired by the contours in topography, this paper proposes a contour method for the population-based stochastic algorithms to solve the problems with continuous variables. Rely...
Ying Lin, Jun Zhang, Lu-kai Lan
GECCO
2010
Springer
163views Optimization» more  GECCO 2010»
13 years 11 months ago
Factors affecting the use of genetic algorithms in test suite augmentation
Test suite augmentation techniques are used in regression testing to help engineers identify code elements affected by changes, and generate test cases to cover those elements. R...
Zhihong Xu, Myra B. Cohen, Gregg Rothermel
CEC
2005
IEEE
14 years 1 months ago
A genetic algorithm for energy minimization in bio-molecular systems
Energy minimization algorithms for bio-molecular systems are critical to applications such as the prediction of protein folding. Conventional energy minimization methods such as th...
Xiaochun Weng, Lutz Hamel, Lenore M. Martin, Joan ...
HIS
2003
13 years 8 months ago
PDGA: the Primal-Dual Genetic Algorithm
Abstract. Genetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. Hence, incorporating mechanisms used in nature may improve the perform...
Shengxiang Yang