FP-AK-QIEAR-R in protein folding application

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Date
2017
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Institute of Electrical and Electronics Engineers Inc.
Abstract
There are many Evolutionary Algorithms which main features are: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like selector. The proposal uses probability density function according to best of initial population to sample new population and save better individuals iteratively. Then using centroid criteria sample for every dimension and get better individuals. It had good results with benchmark functions. A real application was performed with experiments in protein folding and it showed good results. © 2016 IEEE.
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