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» Parameterised system design based on genetic algorithms
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GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
15 years 27 days 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
GECCO
2009
Springer
166views Optimization» more  GECCO 2009»
15 years 6 months ago
Genetic programming in the wild: evolving unrestricted bytecode
We describe a methodology for evolving Java bytecode, enabling the evolution of extant, unrestricted Java programs, or programs in other languages that compile to Java bytecode. B...
Michael Orlov, Moshe Sipper
GECCO
2008
Springer
100views Optimization» more  GECCO 2008»
15 years 27 days ago
Optimizing hierarchical menus by genetic algorithm and simulated annealing
Hierarchical menus are now ubiquitous. The performance of the menu depends on many factors: structure, layout, colors and so on. There has been extensive research on novel menus, ...
Shouichi Matsui, Seiji Yamada
GECCO
2006
Springer
182views Optimization» more  GECCO 2006»
15 years 3 months ago
Distributed genetic algorithm for energy-efficient resource management in sensor networks
In this work we consider energy-efficient resource management in an environment monitoring and hazard detection sensor network. Our goal is to allocate different detection methods...
Qinru Qiu, Qing Wu, Daniel J. Burns, Douglas Holzh...
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
15 years 3 months ago
A hybrid genetic search for multiple sequence alignment
This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It a...
Seung-Hyun Moon, Sung-Soon Choi, Byung Ro Moon