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» Parameterised system design based on genetic algorithms
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ESANN
2008
15 years 7 months ago
Petri nets design based on neural networks
Petri net faulty models are useful for reliability analysis and fault diagnosis of discrete event systems. Such models are difficult to work out as long as they must be computed ac...
Edouard Leclercq, Souleiman Ould el Medhi, Dimitri...
GECCO
2006
Springer
153views Optimization» more  GECCO 2006»
15 years 10 months ago
Analysis of the difficulty of learning goal-scoring behaviour for robot soccer
Learning goal-scoring behaviour from scratch for simulated robot soccer is considered to be a very difficult problem, and is often achieved by endowing players with an innate set ...
Jeff Riley, Victor Ciesielski
DATAMINE
2002
125views more  DATAMINE 2002»
15 years 6 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
ERSA
2006
133views Hardware» more  ERSA 2006»
15 years 7 months ago
An FPGA based Co-Design Architecture for MIMO Lattice Decoders
MIMO systems have attracted great attentions because of their huge capacity. The hardware implementation of MIMO decoder becomes a challenging task as the complexity of the MIMO sy...
Cao Liang, Jing Ma, Xin-Ming Huang
GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
15 years 11 months ago
A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
Federico Divina, Maarten Keijzer, Elena Marchiori