Real-Valued Compact Genetic Algorithms for Embedded Microcontroller Optimization

Recent research on compact genetic algorithms (cGAs) has proposed a number of evolutionary search methods with reduced memory requirements. In cGAs, the evolution of populations is emulated by processing a probability vector with specific update rules. This paper considers the implementation of cGAs...

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Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 12; H. 2; S. 203 - 219
Hauptverfasser:	Mininno, E., Cupertino, F., Naso, D.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.04.2008 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Artificial intelligence Compact genetic algorithms (cGAs) Computational efficiency Computational modeling Computer science; control theory; systems Computer simulation Design optimization electric drives Embedded system embedded systems Encoding Evolutionary Evolutionary algorithms Exact sciences and technology Field programmable gate arrays Genetic algorithms Learning and adaptive systems Mathematical analysis Mathematical models Microcontrollers online optimization Optimization methods Search methods electric drives Compact genetic algorithms (cGAs) online optimization embedded systems Probabilistic approach Microcontroller Evolutionary algorithm Updating Electric drive Optimization Search algorithm Boarded computer Vector processing Genetic algorithm Experimental design Assembler Electric motor
ISSN:	1089-778X, 1941-0026
Online-Zugang:	Volltext
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