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ORCIDGustavo Matheus de Almeida
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2020 – today
- 2024
[c4]Mehar Ullah, Daniel Gutierrez-Rojas, Gustavo Matheus de Almeida, Tero Tynjälä:
Unified Framework to Select an IoT Platform for PtX Cogeneration Plants. MIPRO 2024: 1859-1864- 2023
- [j13]María E. G. Condori, Lucio F. D. Passos, Hugo C. C. Michel
, Gustavo Matheus de Almeida, Marcelo Cardoso:
Dynamic mathematical modelling and simulation of a primary oil separation unit. Int. J. Simul. Process. Model. 20(3): 201-217 (2023) - 2022
- [j12]Daniel Gutierrez-Rojas, Pekka Räsänen, Ana Brandão Belisário, Merim Dzaferagic, Gustavo Matheus de Almeida, Pedro H. J. Nardelli:
Improving Fault Detection in Industrial Processes by Event-Driven Data Acquisition. IEEE Access 10: 80918-80931 (2022) - [j11]Luiz C. B. Torres, Cristiano Leite Castro, Honovan P. Rocha, Gustavo Matheus de Almeida, Antônio P. Braga:
Multi-objective neural network model selection with a graph-based large margin approach. Inf. Sci. 599: 192-207 (2022) - [j10]Iara Campolina Dias Duarte, Gustavo Matheus de Almeida, Marcelo Cardoso:
Heat-loss cycle prediction in steelmaking plants through artificial neural network. J. Oper. Res. Soc. 73(2): 326-337 (2022) - [j9]Hugo D. Rebelo, Lucas A. F. de Oliveira, Gustavo Matheus de Almeida, Cesar Augusto Medina Sotomayor, Vivian S. N. Magalhães, Geraldo L. Rochocz:
Automatic update strategy for real-time discovery of hidden customer intents in chatbot systems. Knowl. Based Syst. 243: 108529 (2022) - [j8]Yuri Sousa Aurelio, Gustavo Matheus de Almeida, Cristiano Leite de Castro, Antônio de Pádua Braga:
Cost-Sensitive Learning based on Performance Metric for Imbalanced Data. Neural Process. Lett. 54(4): 3097-3114 (2022) - 2021
- [j7]Bruna Vajgel, Pedro Luiz Pizzigatti Corrêa, Thais Tóssoli De Sousa, Rosa Virginia Encinas Quille, John A. R. Bedoya, Gustavo Matheus de Almeida, Lucia Vilela Leite Filgueiras, Vanessa Rafaela de Souza Demuner, Denis Mollica:
Development of Intelligent Robotic Process Automation: A Utility Case Study in Brazil. IEEE Access 9: 71222-71235 (2021) - [j6]Hugo D. Rebelo, Lucas A. F. de Oliveira, Gustavo Matheus de Almeida, Cesar Augusto Medina Sotomayor, Geraldo L. Rochocz, Willian E. D. Melo:
Intent Identification in Unattended Customer Queries Using an Unsupervised Approach. J. Inf. Knowl. Manag. 20(3): 2150037:1-2150037:26 (2021) - 2020
- [j5]Ramon Santos Correa, Patricia Teixeira Sampaio, Rafael Utsch Braga, Victor Alberto Lambertucci, Gustavo Matheus de Almeida, Antônio de Pádua Braga:
Prediction of Mechanical Properties of Seamless Steel Tubes Using Artificial Neural Networks. Int. J. Comput. Intell. Appl. 19(4): 2050028:1-2050028:14 (2020) - [c3]Daniel Gutierrez-Rojas, Mehar Ullah, Ioannis T. Christou, Gustavo Matheus de Almeida, Pedro H. J. Nardelli, Dick Carrillo, Jean Michel de Souza Sant'Ana, Hirley Alves, Merim Dzaferagic, Alessandro Chiumento, Charalampos Kalalas:
Three-layer Approach to Detect Anomalies in Industrial Environments based on Machine Learning. ICPS 2020: 250-256 - [i1]Daniel Gutierrez-Rojas, Mehar Ullah, Ioannis T. Christou, Gustavo Matheus de Almeida, Pedro H. J. Nardelli, Dick Carrillo, Jean Michel de Souza Sant'Ana, Hirley Alves, Merim Dzaferagic, Alessandro Chiumento, Charalampos Kalalas:
Three-layer Approach to Detect Anomalies in Industrial Environments based on Machine Learning. CoRR abs/2004.09097 (2020)
2010 – 2019
- 2019
- [j4]Yuri Sousa Aurelio, Gustavo Matheus de Almeida, Cristiano Leite Castro, Antônio de Pádua Braga:
Learning from Imbalanced Data Sets with Weighted Cross-Entropy Function. Neural Process. Lett. 50(2): 1937-1949 (2019) - 2017
- [j3]Alexandre W. C. Faria, Frederico Gualberto F. Coelho, Alisson Marques da Silva, Honovan P. Rocha, Gustavo Matheus de Almeida, André P. Lemos, Antônio P. Braga:
MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation. Eng. Appl. Artif. Intell. 59: 196-204 (2017) - 2016
- [j2]R. N. Lima, Gustavo Matheus de Almeida, Antônio P. Braga, Marcelo Cardoso:
Trend modelling with artificial neural networks. Case study: Operating zones identification for higher SO3 incorporation in cement clinker. Eng. Appl. Artif. Intell. 54: 17-25 (2016) - 2012
- [c2]Gustavo Matheus de Almeida, Song Won Park:
Fault Detection in Continuous Industrial Chemical Processes: A New Approach Using the Hidden Markov Modeling. Case Study: A Boiler from a Brazilian Cellulose Pulp Mill. IDEAL 2012: 743-752 - 2010
- [j1]Gustavo Matheus de Almeida, Marcelo Cardoso, Danilo C. Rena, Song Won Park:
Graphical Representation of Cause-Effect Relationships among Chemical Process Variables Using a Neural Network Approach. Int. J. Comput. Intell. Appl. 9(1): 69-86 (2010)
2000 – 2009
- 2008
- [c1]Gustavo Matheus de Almeida, Marcelo Cardoso, Danilo C. Rena, Song Won Park:
Graphical representation of cause-effect relationships among chemical process variables using a neural network approach. IJCNN 2008: 2668-2673
Coauthor Index
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