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179
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SOCO
2012
Springer
14 years 5 days ago
2012
Springer
Abstract Population-based meta-heuristics are algorithms that can obtain very good results for complex continuous optimization problems in a reduced amount of time. These search al...
178
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AI
2006
Springer
15 years 4 months ago
2006
Springer
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
131
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ICNC
2005
Springer
15 years 10 months ago
2005
Springer
This paper incorporates robustness into neural network modeling and proposes a novel two-phase robustness analysis approach for determining the optimal feedforward neural network (...
169
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IFIP12
2008
15 years 6 months ago
2008
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
140
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CEC
2008
IEEE
15 years 11 months ago
2008
IEEE
— In this paper, we propose a novel approach to solve constrained optimization problems based on particle swarm optimization (PSO). First, an empirical comparison of the most pop...