| Learning from imbalanced data sets with weighted cross-entropy function YS Aurelio, GM De Almeida, CL de Castro, AP Braga Neural processing letters 50, 1937-1949, 2019 | 241 | 2019 |
| Hydrothermal carbonization of lignocellulosic agro-forest based biomass residues CLM Martinez, E Sermyagina, J Saari, MS de Jesus, M Cardoso, ... Biomass and Bioenergy 147, 106004, 2021 | 101 | 2021 |
| Evaluation of thermochemical routes for the valorization of solid coffee residues to produce biofuels: A Brazilian case CLM Martinez, J Saari, Y Melo, M Cardoso, GM de Almeida, ... Renewable and Sustainable Energy Reviews 137, 110585, 2021 | 76 | 2021 |
| Development of intelligent robotic process automation: A utility case study in Brazil B Vajgel, PLP Corrêa, TT De Sousa, RVE Quille, JAR Bedoya, ... Ieee Access 9, 71222-71235, 2021 | 42 | 2021 |
| Fault detection and diagnosis using support vector machines-a SVC and SVR comparison DL de Souza, MH Granzotto, GM de Almeida, LC Oliveira-Lopes Journal of Safety Engineering 3 (1), 18-29, 2014 | 35 | 2014 |
| Predicting kappa number in a kraft pulp continuous digester: A comparison of forecasting methods FM Correia, JVH d'Angelo, GM Almeida, SA Mingoti Brazilian Journal of Chemical Engineering 35, 1081-1094, 2018 | 23 | 2018 |
| Trend modelling with artificial neural networks. Case study: Operating zones identification for higher SO3 incorporation in cement clinker RN Lima, GM de Almeida, AP Braga, M Cardoso Engineering Applications of Artificial Intelligence 54, 17-25, 2016 | 22 | 2016 |
| Fault detection and diagnosis in the DAMADICS benchmark actuator system–A hidden Markov model approach GM de Almeida, SW Park IFAC Proceedings Volumes 41 (2), 12419-12424, 2008 | 20 | 2008 |
| Prediction of mechanical properties of steel tubes using a machine learning approach MV Carneiro, TT Salis, GM Almeida, AP Braga Journal of Materials Engineering and Performance 30 (1), 434-443, 2021 | 17 | 2021 |
| Three-layer approach to detect anomalies in industrial environments based on machine learning D Gutierrez-Rojas, M Ullah, IT Christou, G Almeida, P Nardelli, D Carrillo, ... 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS) 1, 250-256, 2020 | 14 | 2020 |
| MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation AWC Faria, FGF Coelho, AM Silva, HP Rocha, GM Almeida, AP Lemos, ... Engineering Applications of Artificial Intelligence 59, 196-204, 2017 | 11 | 2017 |
| Relatos de experiência de inserção de tecnologias digitais no ensino de engenharia AB Belisário, DG Faria, DH de Souza Chaves, GM de Almeida, ... Revista Docência do Ensino Superior 10, 1-18, 2020 | 9 | 2020 |
| Automatic update strategy for real-time discovery of hidden customer intents in chatbot systems HD Rebelo, LAF de Oliveira, GM Almeida, CAM Sotomayor, ... Knowledge-Based Systems 243, 108529, 2022 | 7 | 2022 |
| Heat-loss cycle prediction in steelmaking plants through artificial neural network ICD Duarte, GM Almeida, M Cardoso Journal of the Operational Research Society 73 (2), 326-337, 2022 | 7 | 2022 |
| Process monitoring in chemical industries–A hidden Markov model approach GM de Almeida, SW Park Proceedings of the 18th European Symposium on Computer Aided Process …, 2008 | 7 | 2008 |
| Fault detection in a sugar evaporation process using hidden Markov models GM Almeida, SW Park ADCONIP'05: proceedings, 2005 | 7 | 2005 |
| 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 GM de Almeida, SW Park Intelligent Data Engineering and Automated Learning-IDEAL 2012: 13th …, 2012 | 6 | 2012 |
| Variables selection for neural networks identification for Kraft recovery boilers GM Almeida, SW Park, M Cardoso IFAC Proceedings Volumes 37 (16), 91-96, 2004 | 6 | 2004 |
| Performance Analysis Method for Robotic Process Automation RVE Quille, FV Almeida, J Borycz, PLP Corrêa, LVL Filgueiras, ... Sustainability 15 (4), 3702, 2023 | 5 | 2023 |
| Improving knowledge about permeability in membrane bioreactors through sensitivity analysis using artificial neural networks AR Alkmim, GM de Almeida, DM de Carvalho, MCS Amaral, ... Environmental Technology 41 (19), 2424-2438, 2020 | 5 | 2020 |
Song Won ParkProfessor Engenharia Quimica, Universidade de Sao Paulo在 usp.br 的电子邮件经过验证
