Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Raúl Hector Gallard"'
Autor:
Daniel Pandolfi, Marta Graciela Lasso, María Eugenia de San Pedro, Andrea Villagra, Raúl Hector Gallard
Publikováno v:
Journal of Computer Science and Technology, Vol 4, Iss 02, Pp 109-114 (2004)
Evolutionary algorithms (EAs) are merely blind search algorithms, which only make use of the relative fitness of solutions, but completely ignore the nature of the problem. Their performance can be improved by using new multirecombinative approaches,
Externí odkaz:
https://doaj.org/article/1bd39e73c60642f79aa2e6a30488d575
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 05, Pp 13 p.-13 p. (2001)
Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most traditional approaches which i
Externí odkaz:
https://doaj.org/article/d3367f02e2ba4419b56fca9d23d3f4e3
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 03, Pp 12 p.-12 p. (2000)
Niche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can be extended to multiobjective
Externí odkaz:
https://doaj.org/article/6aa2ee48497b448da85b3d211bfa0a15
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 03, Pp 10 p.-10 p. (2000)
Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most traditional approaches which i
Externí odkaz:
https://doaj.org/article/d452db4c423548b7a81cd5a374bda562
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 02, Pp 8 p.-8 p. (2000)
As a new promising crossover method, multiple crossovers per couple (MCPC) deserves special attention in evolutionary computing field. Allowing multiple crossovers per couple on a selected pair of parents provided an extra benefit in processing time
Externí odkaz:
https://doaj.org/article/f846d1e808654386be71800678f00cb7
Autor:
Raúl Hector Gallard
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 01, Pp 1 p.-1 p. (1999)
None
Externí odkaz:
https://doaj.org/article/2179a51c65a74f33a13bdd93dd7a442a
Autor:
Claudio Ochoa, Raúl Hector Gallard
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 01, Pp 18 p.-18 p. (1999)
Migration of individuals allows a fruitful interaction between subpopulations in the island model, a well known distributed approach for evolutionary computing, where separate subpopulations evolve in parallel. This model is well suited for a distrib
Externí odkaz:
https://doaj.org/article/9a75151c8f3e4e8fb4f4b34072a768d3
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 01, Pp 14 p.-14 p. (1999)
Fast response, storage efficiency, fault tolerance and graceful degradation in face of scarce or spurious inputs make neural networks appropiate tools for Intelligent Computer Systems. But on the other hand, learning algorithms for neural networks in
Externí odkaz:
https://doaj.org/article/8b7ea79d6a1b49e5a96513c7d8976379
Autor:
Raúl Hector Gallard
Publikováno v:
Journal of Computer Science and Technology, Vol 1, Iss 01, Pp 1 p.-1 p. (1999)
None
Externí odkaz:
https://doaj.org/article/babf174792874831aa4cc20688914420
Publikováno v:
Cybernetics and Systems. 33:559-578
A multiobjective optimization problem involves multiple objectives, often conflicting, to be met or optimized. A Pareto front provides a set of best solutions to determine the trade-offs between the various objectives. New evolutionary approaches dem