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The compact Genetic Algorithm for likelihood estimator of first order moving average model
2012
2012 Second International Conference on Digital Information and Communication Technology and it's Applications (DICTAP)
Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically
doi:10.1109/dictap.2012.6215410
dblp:conf/dictap/Al-DabbaghBMK12
fatcat:kd4sil2govbvfp5n6nhzdu4ywm