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» A Comparison of Genetic Network Models
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GECCO
2004
Springer
103views Optimization» more  GECCO 2004»
15 years 3 months ago
Training Neural Networks with GA Hybrid Algorithms
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
Enrique Alba, J. Francisco Chicano
GECCO
2010
Springer
154views Optimization» more  GECCO 2010»
15 years 2 months ago
Evolutionary learning in networked multi-agent organizations
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
Jae-Woo Kim
BMCBI
2005
120views more  BMCBI 2005»
14 years 9 months ago
SpectralNET - an application for spectral graph analysis and visualization
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...
URBAN
2008
99views more  URBAN 2008»
14 years 9 months ago
A comparison of address point, parcel and street geocoding techniques
The widespread availability of powerful geocoding tools in commercial GIS software and the interest in spatial analysis at the individual level have made address geocoding a widel...
Paul A. Zandbergen
ICDCN
2009
Springer
15 years 4 months ago
Self-similar Functions and Population Protocols: A Characterization and a Comparison
Chandy et al. proposed the methodology of “self-similar algorithms” for distributed computation in dynamic environments. We further characterize the class of functions computab...
Swapnil Bhatia, Radim Bartos