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» On Genetic Algorithms and Lindenmayer Systems
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TEC
2008
93views more  TEC 2008»
15 years 6 months ago
The Self-Organization of Interaction Networks for Nature-Inspired Optimization
Over the last decade, significant progress has been made in understanding complex biological systems, however there have been few attempts at incorporating this knowledge into natu...
James M. Whitacre, Ruhul A. Sarker, Q. Tuan Pham
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
15 years 11 months ago
A comparison of evolutionary algorithms for system-level diagnosis
The size and complexity of systems based on multiple processing units demand techniques for the automatic diagnosis of their state. System-level diagnosis consists in determining ...
Bogdan Tomoyuki Nassu, Elias Procópio Duart...
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
15 years 7 months ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi
ARCS
2007
Springer
15 years 10 months ago
Toward Self-adaptive Embedded Systems: Multi-objective Hardware Evolution
Abstract. Evolutionary hardware design reveals the potential to provide autonomous systems with self-adaptation properties. We first outline an architectural concept for an intrins...
Paul Kaufmann, Marco Platzner
AEI
1999
110views more  AEI 1999»
15 years 6 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga