Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Josiane da Costa Vieira Rezende"'
Autor:
Renato de Aguiar Corrêa, Jurema Suely de Araújo Nery Ribeiro, Fábio Corrêa, Frederico Giffoni de Carvalho Dutra, Josiane da Costa Vieira Rezende
Publikováno v:
Perspectivas em Ciência da Informação, Vol 29 (2024)
RESUMO Este estudo se concentra na aplicação prática da Gestão do Conhecimento (GC) em Redes Confessionais de Ensino em Belo Horizonte, MG. Este estudo tem como objetivo principal propor estratégias de melhoria para elevar o nível de maturidade
Externí odkaz:
https://doaj.org/article/279b898fe8cb4fe7abef4e0cb1b3310e
Publikováno v:
Sensors, Vol 20, Iss 23, p 6954 (2020)
The benefits of using mobile sinks or data mules for data collection in Wireless Sensor Network (WSN) have been studied in several works. However, most of them consider only the WSN limitations and sensor nodes having no more than one data packet to
Externí odkaz:
https://doaj.org/article/04a8be7661e24a3086cfe9852bb18623
Autor:
Marcone Jamilson Freitas Souza, Alexandre Xavier Martins, Josiane da Costa Vieira Rezende, Vitor Nazário Coelho
Publikováno v:
Electronic Notes in Discrete Mathematics. 66:7-14
This work presents a hybrid multi-start algorithm for solving generic binary linear programs. This algorithm, called HMS, is based on a Multi-Start Metaheuristic and combines exact and heuristic strategies to address the problem. The initial solution
Publikováno v:
Sensors, Vol 20, Iss 6954, p 6954 (2020)
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 23
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 23
The benefits of using mobile sinks or data mules for data collection in Wireless Sensor Network (WSN) have been studied in several works. However, most of them consider only the WSN limitations and sensor nodes having no more than one data packet to
Publikováno v:
CLEI
In this paper it is proposed a hybrid algorithm, so-called HGVPRLB, for solving generic binary problems. The algorithm HGVPRLB combines the heuristic procedures GRASP, Variable Neighborhood Descent, Constraint Propagation and Local Branching Cuts. It