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Detalhes

Detalhes

004
Publicações

2023

Stochastic crowd shipping last-mile delivery with correlated marginals and probabilistic constraints

Autores
Silva, M; Pedroso, JP; Viana, A;

Publicação
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract

2023

A data-driven compensation scheme for last-mile delivery with crowdsourcing

Autores
Barbosa, M; Pedroso, JP; Viana, A;

Publicação
COMPUTERS & OPERATIONS RESEARCH

Abstract

2023

Deep reinforcement learning for stochastic last-mile delivery with crowdshipping

Autores
Silva, M; Pedroso, JP; Viana, A;

Publicação
EURO JOURNAL ON TRANSPORTATION AND LOGISTICS

Abstract

2022

The Sea Exploration Problem Revisited

Autores
Dionisio, J; dos Santos, D; Pedroso, JP;

Publicação
MACHINE LEARNING, OPTIMIZATION, AND DATA SCIENCE (LOD 2021), PT I

Abstract

2022

Mapping Cashew Orchards in Cantanhez National Park (Guinea-Bissau)

Autores
Pereira, SC; Lopes, C; Pedroso, JP;

Publicação
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT

Abstract
The forests and woodlands of Guinea-Bissau are a biodiversity hotspot under threat, which are progressively being replaced by cashew tree orchards. While the exports of cashew nuts significantly contribute to the gross domestic product and support local livelihoods, the country's natural capital is under significant pressure due to unsustainable land use. In this context, official entities strive to counter deforestation, but the problem persists, and there are currently no systematic or automated means for objectively monitoring and reporting the situation. Furthermore, previous remote sensing approaches failed to distinguish cashew orchards from forests and woodlands due to the significant spectral overlap between the land cover types and the highly intertwined structure of the cashew tree patches. This work contributes to overcoming such difficulty. It develops an affordable, reliable, and easy-to-use procedure based on machine learning models and Sentinel-2 images, automatically detecting cashew orchards with a dice coefficient of 82.54%. The results of this case study designed for the Cantanhez National Park are proof of concept and demonstrate the viability of mapping cashew orchards. Therefore, the work is a stepping stone towards wall-to-wall operational monitoring in the region. © 2022 Elsevier B.V.

Teses
supervisionadas

2022

Optimization models for maintenance

Autor
João Pedro Gonçalves Dionísio

Instituição
UP-FCUP

2022

Connecting quantum computing and machine learning to improve quantum simulation and optimization

Autor
Pedro Miguel Miranda Queiroz da Cruz

Instituição
UP-FCUP

2022

Automated Physical Law Discovery from Data using Physics Informed Machine Learning

Autor
José Miguel de Oliveira Bastos

Instituição
UP-FEUP

2022

Monitoring Greenhouses with Satellite Images and Machine Learning

Autor
Pedro Miguel Pereira Cardoso

Instituição
UP-FCUP

2021

Connecting quantum computing and machine learning to improve quantum simulation and optimization

Autor
Pedro Miguel Miranda Queiroz da Cruz

Instituição
UP-FCUP