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CORR
2004
Springer
87views Education» more  CORR 2004»
13 years 4 months ago
Exploring tradeoffs in pleiotropy and redundancy using evolutionary computing
Evolutionary computation algorithms are increasingly being used to solve optimization problems as they have many advantages over traditional optimization algorithms. In this paper...
Matthew J. Berryman, Wei-Li Khoo, Hiep Nguyen, Eri...
CORR
2004
Springer
81views Education» more  CORR 2004»
13 years 4 months ago
Optimizing genetic algorithm strategies for evolving networks
This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best...
Matthew J. Berryman, Andrew Allison, Derek Abbott
SBRN
2000
IEEE
13 years 9 months ago
An Evolutionary Immune Network for Data Clustering
This paper explores basic aspects of the immune system and proposes a novel immune network model with the main goals of clustering and filtering unlabeled numerical data sets. It ...
Leandro Nunes de Castro, Fernando J. Von Zuben
VLSID
2002
IEEE
138views VLSI» more  VLSID 2002»
14 years 5 months ago
A Framework for Design Space Exploration of Parameterized VLSI Systems
The paper presents two new approaches to multiobjective design space exploration for parametric VLSI systems. Both considerably reduce the number of simulations needed to determin...
Giuseppe Ascia, Vincenzo Catania, Maurizio Palesi
NCA
2007
IEEE
13 years 4 months ago
Using evolution to improve neural network learning: pitfalls and solutions
: Autonomous neural network systems typically require fast learning and good generalization performance, and there is potentially a trade-off between the two. The use of evolutiona...
John A. Bullinaria