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A parallel ant colony optimization algorithm based on crossover operation
Date
2018-11-01
Author
Kalınlı, Adem
Sarıkoç, Fatih
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In this work, we introduce a new parallel ant colony optimization algorithm based on an ant metaphor and the crossover operator from genetic algorithms.The performance of the proposed model is evaluated usingwell-known numerical test problems and then it is applied to train recurrent neural networks to identify linear and nonlinear dynamic plants. The simulation results are compared with results using other algorithms.
Subject Keywords
Recurrent neural network
,
Crossover operation
,
Elman network
,
Linear plant
,
Pheromone matrix
URI
https://hdl.handle.net/11511/84554
Relation
Advances in metaheuristics for hard optimization
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BibTeX
A. Kalınlı and F. Sarıkoç,
A parallel ant colony optimization algorithm based on crossover operation
. 2018, p. 110.