Multi-Objective Decision-Making Meets Dynamic Shortest Path: Challenges and Prospects

Autor: Juarez Machado da Silva, Gabriel de Oliveira Ramos, Jorge Luis Victória Barbosa

Publikováno v: Algorithms, Vol 16, Iss 3, p 162 (2023)

The Shortest Path (SP) problem resembles a variety of real-world situations where one needs to find paths between origins and destinations. A generalization of the SP is the Dynamic Shortest Path (DSP) problem, which also models changes in the graph

Externí odkaz: https://doaj.org/article/7394ebcaa3c847b6b7958d032f33afb9

Multilevel Optimization Applied to Project of Access Networks for Implementation of Intelligent Cities

Autor: Márcio Joel Barth, Leandro Mengue, Juarez Machado da Silva, Jorge Luis Victória Barbosa, Marcelo Josué Telles, José Vicente Canto dos Santos

Publikováno v: Urban Computing ISBN: 9783030122546
Smart and Digital Cities

Studies about network infrastructure have been realized and applied in a high variety of service-based industries, these studies are currently being used to design the network infrastructure in smart cities. However, planning network infrastructure i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::79c42f5bc452744f8fa4a454749f7765
https://doi.org/10.1007/978-3-030-12255-3_7

Proposal of a method to determine the correlation between total suspended solids and dissolved organic matter in water bodies from spectral imaging and artificial neural networks

Autor: Lucas Silveira Kupssinskü, Ismael Érique Koch, Luiz Gonzaga, Frederico Fábio Mauad, Rogélio S. Jardim, Juarez Machado da Silva, Fabiane Bordin, Laís Vieira de Souza, Jonas G. de Souza, Mauricio Roberto Veronez, William Ferreira Moreno Oliverio, Tainá Thomassim Guimarães, Leonardo Campos Inocencio, Emilie C. Koste

Publikováno v: Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Sensors (Basel, Switzerland)
Sensors, Vol 18, Iss 1, p 159 (2018)

Water quality monitoring through remote sensing with UAVs is best conducted using multispectral sensors; however, these sensors are expensive. We aimed to predict multispectral bands from a low-cost sensor (R, G, B bands) using artificial neural netw

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec81c0548fa929d2d9668dd54588c912