Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Edgar Galván-López"'
The three papers in this special section focus on data driven computational intelligence for electronic governance, socio-political and economic systems. These papers reflect the design and development of computational tools and systems to exploit da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a006d417c7fc330e8eccf4eb8b06217e
https://mural.maynoothuniversity.ie/12675/
https://mural.maynoothuniversity.ie/12675/
Publikováno v:
EA 2017-International Conference on Artificial Evolution
EA 2017-International Conference on Artificial Evolution, Evelyne Lutton, Oct 2017, Paris, France. pp.1-14
Lecture Notes in Computer Science ISBN: 9783319781327
Artificial Evolution
EA 2017-International Conference on Artificial Evolution, Evelyne Lutton, Oct 2017, Paris, France. pp.1-14
Lecture Notes in Computer Science ISBN: 9783319781327
Artificial Evolution
International audience; In Genetic Programming (GP), the fitness of individuals is normally computed by using a set of fitness cases (FCs). Research on the use of FCs in GP has primarily focused on how to reduce the size of these sets. However, often
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::110b4ad0f2b41439b75cd863f62b6e11
https://hal.inria.fr/hal-01648365
https://hal.inria.fr/hal-01648365
Publikováno v:
GECCO (Companion)
In Genetic Programming (GP), the fitness of individuals is normally computed by using a set of fitness cases (FCs). Research on the use of FCs in GP has primarily focused on how to reduce the size of these sets to, for instance, reduce the fitness ev
Publikováno v:
Advances in Soft Computing ISBN: 9783319624273
MICAI (2)
MICAI (2)
Data sets with imbalanced class distribution pose serious challenges to well-established classifiers. In this work, we propose a stochastic multi-objective genetic programming based on semantics. We tested this approach on imbalanced binary classific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6df5f20d54506410fac08dfae1d1f96f
https://doi.org/10.1007/978-3-319-62428-0_22
https://doi.org/10.1007/978-3-319-62428-0_22
Autor:
Edgar Galván-López, Ouassim Ait ElHara
Publikováno v:
SSCI
In Evolutionary Algorithms (EAs), it is well-known that the adoption of diversity is highly beneficial for evolutionary search. This has also been explored and confirmed in Dynamic Optimisation Problems (DOPs) using EAs. Multiple works have been prop
Publikováno v:
Studies in Computational Intelligence ISBN: 9783319485041
IJCCI (Selected Papers)
IJCCI (Selected Papers)
In this paper, we investigate the use of an stochastic optimisation bio-inspired algorithm, differential evolution, and proposed two fitness (cost) functions that can automatically create an intelligent scheduling for a demand-side management system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f015e33a070dc3e0ed3b62d767f6767
https://doi.org/10.1007/978-3-319-48506-5_9
https://doi.org/10.1007/978-3-319-48506-5_9
We propose a GP algorithm with intrinsic bloat control properties, called neat-GP.The algorithm combines the insights gained from the Operator and NEAT.The proposal is efficient and applicable to symbolic regression and classification. Bloat is one o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abdecbb2975e0d397e22484a1bfd9e51
http://mural.maynoothuniversity.ie/12330/
http://mural.maynoothuniversity.ie/12330/
Publikováno v:
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines, Springer Verlag, 2016, 17 (4), pp.409-449. ⟨10.1007/s10710-016-9265-9⟩
Genetic Programming and Evolvable Machines, 2016, 17 (4), pp.409-449. ⟨10.1007/s10710-016-9265-9⟩
Genetic Programming and Evolvable Machines, Springer Verlag, 2016, 17 (4), pp.409-449. ⟨10.1007/s10710-016-9265-9⟩
Genetic Programming and Evolvable Machines, 2016, 17 (4), pp.409-449. ⟨10.1007/s10710-016-9265-9⟩
International audience; The study of problem difficulty is an open issue in Genetic Programming (GP). Thegoal of this work is to generate models that predict the expected performance of a GPbasedclassifier when it is applied to an unseen task. Classi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b635fa9c862d43e62e5cc6ccd2505214
https://hal.inria.fr/hal-01252141
https://hal.inria.fr/hal-01252141
Publikováno v:
Parallel Problem Solving from Nature – PPSN XIV ISBN: 9783319458229
PPSN
14th International Conference Parallel Problem Solving from Nature – PPSN XIV
14th International Conference Parallel Problem Solving from Nature – PPSN XIV, Sep 2016, Edinburgh, United Kingdom. pp.353-363, ⟨10.1007/978-3-319-45823-6_33⟩
PPSN
14th International Conference Parallel Problem Solving from Nature – PPSN XIV
14th International Conference Parallel Problem Solving from Nature – PPSN XIV, Sep 2016, Edinburgh, United Kingdom. pp.353-363, ⟨10.1007/978-3-319-45823-6_33⟩
International audience; Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Motivated by these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::605ba7aa2e8e1b5acd6216991a71d7d8
https://doi.org/10.1007/978-3-319-45823-6_33
https://doi.org/10.1007/978-3-319-45823-6_33
Publikováno v:
Evolving Systems. 2:145-163
Over the last years, the effects of neutrality have attracted the attention of many researchers in the Evolutionary Algorithms (EAs) community. A mutation from one gene to another is considered as neutral if this modification does not affect the phen