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» Modeling GA Performance for Control Parameter Optimization
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BMCBI
2010
185views more  BMCBI 2010»
14 years 9 months ago
MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heu
Background: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most compara...
Raphaël Helaers, Michel C. Milinkovitch
ACIIDS
2009
IEEE
105views Database» more  ACIIDS 2009»
15 years 9 days ago
Stability Analysis of Fuzzy Control for Nonlinear Systems
In this study, we propose a method of stability analysis for a GA-Based reference ANNC capable of handling these types of problems for a nonlinear system. The initial values of the...
Po-Chen Chen, Ken Yeh, Cheng-Wu Chen, Shu-Hao Lin
APNOMS
2006
Springer
15 years 6 months ago
Parameter Design for Diffusion-Type Autonomous Decentralized Flow Control
We have previously proposed a diffusion-type flow control mechanism as a solution for severely time-sensitive flow control required for high-speed networks. In this mechanism, each...
Chisa Takano, Keita Sugiyama, Masaki Aida
WSC
2007
15 years 4 months ago
Optimal scheduling of probabilistic repetitive projects using completed unit and genetic algorithms
In this paper we introduce the completed unit algorithm (CU-AL), a probabilistic scheduling methodology for repetitive projects. The algorithm has two main advantages, simplicity ...
Chachrist Srisuwanrat, Photios G. Ioannou
JUCS
2007
107views more  JUCS 2007»
15 years 2 months ago
Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Processes
: A genetic algorithm (GA) based recurrent fuzzy neural network modeling method for dynamic nonlinear chemical process is presented. The dynamic recurrent fuzzy neural network (RFN...
Jili Tao, Ning Wang, Xuejun Wang