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» Evolving Complex Neural Networks
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BIBE
2007
IEEE
124views Bioinformatics» more  BIBE 2007»
15 years 4 months ago
Finding Cancer-Related Gene Combinations Using a Molecular Evolutionary Algorithm
—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
AAAI
2007
15 years 7 days ago
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution
Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
Bobby D. Bryant, Risto Miikkulainen
ISNN
2007
Springer
15 years 4 months ago
Recurrent Fuzzy CMAC for Nonlinear System Modeling
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...
Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moren...
EPS
1995
Springer
15 years 1 months ago
PANIC: A Parallel Evolutionary Rule Based System
PANIC (Parallelism And Neural networks In Classifier systems) is a parallel system to evolve behavioral strategies codified by sets of rules. It integrates several adaptive techni...
Antonella Giani, Fabrizio Baiardi, Antonina Starit...
SMC
2007
IEEE
122views Control Systems» more  SMC 2007»
15 years 4 months ago
Can complexity science support the engineering of critical network infrastructures?
— Considerable attention is now being devoted to the study of “complexity science” with the intent of discovering and applying universal laws of highly interconnected and evo...
David Alderson, John C. Doyle