Study of Fuzzy Cognitive Maps to Model Inverse Problems

• Grant number: 24/06949-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2024
• End date: December 31, 2024
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Applied Mathematics
• Principal Investigator: Vinícius Francisco Wasques
• Grantee: Vitória Yumi Uetuki Nicoleti
• Host Institution: Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Campinas , SP, Brazil

Abstract

This project proposes the study of modeling Inverse Problems using Fuzzy Cognitive Maps, aiming to understand the cognitive process involved in a network. Specifically, some of the uncertainties that exist in inverse problems arising from computed tomography will be addressed, using as scientific motivation some of the beamlines from the synchrotron light accelerator of the Brazilian Center for Research in Energy and Materials, Sirius. These Inverse Problems modeling will be interpreted by Fuzzy Cognitive Maps, a tool established in the literature that allows the analysis of these uncertainties. Using the Open-Science principle, we will use tomographic data obtained through open repositories and in line with scientific developments coordinated by the researcher and project co-advisor Eduardo Xavier Silva Miqueles, for Sirius. Thus, we will seek to simulate different scenarios and propose solutions to such problems.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

SILVA, MONYQUE KAROLINE DE PAULA; NICOLETI, VITORIA YUMI UETUKI; RODRIGUES, BARBARA DA PAIXAO PEREZ; ARAUJO, ADEMIR SERGIO FERREIRA; ELLWANGER, JOEL HENRIQUE; DE ALMEIDA, JAMES MORAES; LEMOS, LEANDRO NASCIMENTO. Exploring deep learning in phage discovery and characterization. VIROLOGY, v. 609, p. 11-pg., 2025-05-12. (24/05797-9, 24/06949-7)