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HIGH-PERFORMANCE COMPUTING MEMETIC ALGORITHM (HPCMA) MODEL TO PROCESS IMAGE FINGERPRINT DATASET
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The terminology of the memetic refers to “meme”. The meme is a part of natural information of the
individual population and this information can be transmitted among the individual of the population. The memetic
algorithm (MA) uses the evolutionary concept based on the Genetic Algorithm (GA) and is combined with a local
search feature. Thus, as in GA, MA employs the basic steps such as selection, crossover, and mutation with additional
components a local search to improve the solution of candidates. The major challenge of this algorithm is how to
develop a good local search operator that can do a good exploration of the entire population. Several methods have
been proposed and we have studied several parallel methods implemented on MA (PMA) to increase the efficiency of
processing time. The parallel method is included in cluster computing, and that is a part of high-performance
computing systems. In this work, we proposed the two new models of the memetic algorithm that run in a high performance computing system (HPCMA) environment by utilizing the multi-threads feature of processor, so-called
HPCMA1 and HPCMA2 model, to process fingerprints image dataset. The result shows that the HPCMA1 model runs
with high inconsistency data caused by its overlaps in the macro-process and to address the problem from the
HPCMA1 model we use the HPCMA2 model.
PRIATI ASSIROJ - Personal Name
Harco Leslie Hendric Spits Warnars - Personal Name
Edi Abdurachman - Personal Name
ACHMAD IMAM KISTIJANTORO - Personal Name
ANTOINE DOUCET - Personal Name
Harco Leslie Hendric Spits Warnars - Personal Name
Edi Abdurachman - Personal Name
ACHMAD IMAM KISTIJANTORO - Personal Name
ANTOINE DOUCET - Personal Name
1927-5307
NONE
electronic file
English
SCIK Publishing Corporation
2021
United Kingdom
Vol. 11, Jil.11, Terbitan 4, Hlm.3813-3828
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