Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Mario Tasso Ribeiro Serra Neto"'
Autor:
Otávio Noura Teixeira, Mario Tasso Ribeiro Serra Neto, Daniel Leal Souza, Roberto Célio Limão de Oliveira, Rodrigo Lisboa Pereira, Marco Antonio Florenzano Mollinetti
Publikováno v:
IEEE Access. 11:12150-12175
The Multi-Swarm approach allows the use of multiple configurations between two or more populations of particles, where each one can present different approaches (e.g. lbest, gbest, Unified, Guaranteed-Convergence) directed towards improving the optim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db048ecb3adf1e4cef25d714f729b0cd
https://doi.org/10.1109/access.2021.3119579
https://doi.org/10.1109/access.2021.3119579
Autor:
Marco Antonio Florenzano Mollinetti, Bernardo B. Gatto, Takahito Kuno, Mario Tasso Ribeiro Serra Neto
Publikováno v:
Entropy
Entropy, Vol 22, Iss 1004, p 1004 (2020)
Volume 22
Issue 9
Entropy, Vol 22, Iss 1004, p 1004 (2020)
Volume 22
Issue 9
Artificial Bee Colony (ABC) is a Swarm Intelligence optimization algorithm well known for its versatility. The selection of decision variables to update is purely stochastic, incurring several issues to the local search capability of the ABC. To addr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e83f4feedd518c5f2caa0950f483e322
http://europepmc.org/articles/PMC7597078
http://europepmc.org/articles/PMC7597078
Autor:
Bernardo B. Gatto, Marco Antonio Florenzano Mollinetti, Takahito Kuno, Mario Tasso Ribeiro Serra Neto
Publikováno v:
Anais do XVI Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2019).
Artificial Bee Colony (ABC) is a Swarm Intelligence optimization algorithm well-know for its versatility. The selection of decision variables to up-date is purely stochastic, incurring in several issues to the local search capability of the ABC. To a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afecbc464121fd505f6975ad2c8790dc
https://doi.org/10.5753/eniac.2019.9325
https://doi.org/10.5753/eniac.2019.9325
Publikováno v:
Hybrid Intelligent Systems ISBN: 9783030143466
HIS
HIS
Artificial Bee Colony (ABC) is a bee inspired swarm intelligence (SI) algorithm well-known for its versatility and simplicity. In crucial steps of the algorithm, employed and scout bees phase, parameters (decision variables) are chosen in a random fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f3a2a4208ef9c08f2abdd877d3dbcff
https://doi.org/10.1007/978-3-030-14347-3_9
https://doi.org/10.1007/978-3-030-14347-3_9
Autor:
Marco Antonio Florenzano Mollinetti, Vladimiro Miranda, Mario Tasso Ribeiro Serra Neto, Leonel M. Carvalho
Publikováno v:
Progress in Artificial Intelligence ISBN: 9783030302405
EPIA (1)
EPIA (1)
The following paper presents a novel strategy named Maximum Search Limitations (MS) for the Evolutionary Particle Swarm Optimization (EPSO). The approach combines EPSO standard search mechanism with a set of rules and position-wise statistics, allowi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b84b3f1b44aceec264e431a1afca5141
https://doi.org/10.1007/978-3-030-30241-2_59
https://doi.org/10.1007/978-3-030-30241-2_59
Autor:
Marco Antonio Florenzano Mollinetti, Adilson de Almeida Neto, Roberto Célio Limão de Oliveira, Otávio Noura Teixeira, Rodrigo Lisboa Pereira, Mario Tasso Ribeiro Serra Neto, Daniel Leal Souza, Edson Koiti Kudo Yasojima
Publikováno v:
CEC
This article presents a parameter study on the applied game theory in Genetic Algorithm (GA), performing an analysis of the game Prisoner's Dilemma applied in the solution of four constrained Engineering problems. Simulations were applied in four dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::946c0eda64c518ca6434dcab2b24713f
https://doi.org/10.1109/cec.2018.8477925
https://doi.org/10.1109/cec.2018.8477925
CEMCO: A Novel Competitive Evolutionary Multi-Colony Optimization Algorithm for Constrained Problems
Autor:
Mario Tasso Ribeiro Serra Neto, Demison Rolins de Souza Alves, Otávio Noura Teixeira, Rodrigo Lisboa Pereira, Marco Antonio Florenzano Mollinetti
Publikováno v:
ICNC-FSKD
The following paper presents a hybrid Swarm Intelligence algorithm, named Competitive Evolutionary Multi-Colony Optimization (CEMCO). CEMCO is based on the well-known bee inspired algorithm Artificial Bee Colony (ABC), introducing Evolutionary Strate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::921f47b224cf8bb5f734436504e1cbab
https://doi.org/10.1109/fskd.2018.8687150
https://doi.org/10.1109/fskd.2018.8687150
Autor:
Otávio Noura Teixeira, Mario Tasso Ribeiro Serra Neto, Fabio dos Santos Ferreira, Demison Rolins de Souza Alves
Publikováno v:
ICMLSC
The following paper demonstrates the possibilities of adapting the Ant Colony Algorithm with Social Interaction coming from Game Theory. This novel algorithm, named Social Interaction Ant Colony Optimization (SIACO), were based on the Ant System Algo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85d9273400d5faa0672a4772550dc6cb
https://doi.org/10.1145/3184066.3184077
https://doi.org/10.1145/3184066.3184077
Autor:
Demison Rolins de Souza Alves, Otávio Noura Teixeira, Fabio dos Santos Ferreira, Mario Tasso Ribeiro Serra Neto, Daniel Leal Souza, Rodrigo Lisboa Pereira, Marco Antonio Florenzano Mollinetti
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783319912615
ICAISC (2)
ICAISC (2)
The Artificial Bee Colony (ABC) is a well-known simple and efficient bee inspired metaheuristic that has been showed to achieve good performance on real valued optimization problems. Inspired by such, a Quick Artificial Bee Colony (QABC) was proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a943b2e9cefa6ccd1b3e15e02c86da4e
https://doi.org/10.1007/978-3-319-91262-2_53
https://doi.org/10.1007/978-3-319-91262-2_53
Publikováno v:
ICNC-FSKD
The Artificial Bee Colony is a popular simple and efficient bee inspired metaheuristic that showed good performance on real valued optimization problems. To improve its local search capabilities, a modified version of it, called ABC+ES was proposed.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cad564caedd662aaaae1b6b695d7094
https://doi.org/10.1109/fskd.2017.8393309
https://doi.org/10.1109/fskd.2017.8393309