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GECCO
2004
Springer
13 years 10 months ago
Shortcomings with Tree-Structured Edge Encodings for Neural Networks
In evolutionary algorithms a common method for encoding neural networks is to use a tree-structured assembly procedure for constructing them. Since node operators have difficulties...
Gregory Hornby
GPEM
2006
82views more  GPEM 2006»
13 years 4 months ago
Shortcomings with using edge encodings to represent graph structures
There are various representations for encoding graph structures, such as artificial neural networks (ANNs) and circuits, each with its own strengths and weaknesses. Here we analyz...
Gregory Hornby
IADIS
2008
13 years 6 months ago
Fuzzy Association Rule Reduction Using Clustering In Som Neural Network
The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many ...
Marjan Kaedi, Mohammad Ali Nematbakhsh, Nasser Gha...
APIN
2004
107views more  APIN 2004»
13 years 4 months ago
Designing Polymer Blends Using Neural Networks, Genetic Algorithms, and Markov Chains
In this paper we present a new technique to simulate polymer blends that overcomes the shortcomings in polymer system modeling. This method has an inherent advantage in that the v...
N. K. Roy, Walter D. Potter, D. P. Landau
ICIP
2003
IEEE
14 years 6 months ago
Image compression with on-line and off-line learning
Images typically contain smooth regions, which are easily compressed by linear transforms, and high activity regions (edges, textures), which are harder to compress. To compress t...
Patrice Y. Simard, Christopher J. C. Burges, David...