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» Particle Swarm Optimization Using Adaptive Mutation
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TEC
1998
106views more  TEC 1998»
14 years 9 months ago
Combining mutation operators in evolutionary programming
Abstract— Traditional investigations with evolutionary programming (EP) for continuous parameter optimization problems have used a single mutation operator with a parameterized p...
Kumar Chellapilla
ICIC
2009
Springer
14 years 7 months ago
Inference of Differential Equation Models by Multi Expression Programming for Gene Regulatory Networks
This paper presents an evolutionary method for identifying the gene regulatory network from the observed time series data of gene expression using a system of ordinary differential...
Bin Yang, Yuehui Chen, Qingfang Meng
62
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AHS
2006
IEEE
161views Hardware» more  AHS 2006»
15 years 3 months ago
A Self-Tuning Analog Proportional-Integral-Derivative (PID) Controller
We present a framework for a low power self-tuning analog proportional-integral-derivative controller. By using a model-free tuning method, it overcomes problems associated with r...
Varun Aggarwal, Meng Mao, Una-May O'Reilly
GECCO
2009
Springer
126views Optimization» more  GECCO 2009»
15 years 2 months ago
Improving NSGA-II with an adaptive mutation operator
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters pre...
Arthur Gonçalves Carvalho, Aluizio F. R. Ar...
JGO
2010
121views more  JGO 2010»
14 years 8 months ago
The oracle penalty method
A new and universal penalty method is introduced in this contribution. It is especially intended to be applied in stochastic metaheuristics like genetic algorithms, particle swarm...
Martin Schlüter, Matthias Gerdts