| A lithology identification approach based on machine learning with evolutionary parameter tuning CM Saporetti, LG da Fonseca, E Pereira IEEE Geoscience and Remote Sensing Letters 16 (12), 1819-1823, 2019 | 80 | 2019 |
| Machine learning approaches for petrographic classification of carbonate-siliciclastic rocks using well logs and textural information CM Saporetti, LG da Fonseca, E Pereira, LC de Oliveira Journal of Applied Geophysics 155, 217-225, 2018 | 69 | 2018 |
| Neural network boosted with differential evolution for lithology identification based on well logs information CM Saporetti, L Goliatt, E Pereira Earth Science Informatics 14 (1), 133-140, 2021 | 38 | 2021 |
| Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields CM Saporetti, DL Fonseca, LC Oliveira, E Pereira, L Goliatt Marine and Petroleum Geology 143, 105783, 2022 | 33 | 2022 |
| Extreme learning machine combined with a differential evolution algorithm for lithology identification CM Saporetti, GR Duarte, TL Fonseca, LG da Fonseca, E Pereira Revista de Informática Teórica e Aplicada 25 (4), 43-56, 2018 | 31 | 2018 |
| Approaches for the short-term prediction of natural daily streamflows using hybrid machine learning enhanced with grey wolf optimization AD Martinho, CM Saporetti, L Goliatt Hydrological Sciences Journal 68 (1), 16-33, 2023 | 21 | 2023 |
| Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields L Goliatt, CM Saporetti, LC Oliveira, E Pereira Petroleum 10 (1), 150-164, 2024 | 17 | 2024 |
| Super learner approach to predict total organic carbon using stacking machine learning models based on well logs L Goliatt, CM Saporetti, E Pereira Fuel 353, 128682, 2023 | 13 | 2023 |
| Machine learning with model selection to predict TOC from mineralogical constituents: case study in the Sichuan Basin CM Saporetti, DL Fonseca, LC Oliveira, E Pereira, L Goliatt International Journal of Environmental Science and Technology 20 (2), 1585-1596, 2023 | 12 | 2023 |
| Global horizontal irradiance modeling from environmental inputs using machine learning with automatic model selection SCA Basílio, CM Saporetti, ZM Yaseen, L Goliatt Environmental Development 44, 100766, 2022 | 9 | 2022 |
| Evolutionary automated radial basis function neural network for multiphase flowing bottom-hole pressure prediction D Campos, DDK Wayo, RB De Santis, DA Martyushev, ZM Yaseen, ... Fuel 377, 132666, 2024 | 7 | 2024 |
| An approach for total organic carbon prediction using convolutional neural networks optimized by differential evolution RO Silva, CM Saporetti, ZM Yaseen, E Pereira, L Goliatt Neural Computing and Applications 35 (28), 20803-20817, 2023 | 6 | 2023 |
| Data-driven cymbal bronze alloy identification via evolutionary machine learning with automatic feature selection THA Boratto, CM Saporetti, SCA Basilio, AA Cury, L Goliatt Journal of Intelligent Manufacturing 35 (1), 257-273, 2024 | 5 | 2024 |
| An interdependent evolutionary machine learning model applied to global horizontal irradiance modeling SCA Basílio, CM Saporetti, L Goliatt Neural Computing and Applications 35 (16), 12099-12120, 2023 | 5 | 2023 |
| Hybrid machine learning approaches enhanced with grey wolf optimization to short-term prediction of natural daily streamflows A Martinho, C Saporetti, L Goliatt Hydrol. Sci. J 20, 20, 2022 | 5 | 2022 |
| Hybrid unsupervised extreme learning machine applied to facies identification CM Saporetti, IGL Rosa, RM Carvalho, E Pereira, LG da Fonseca Proceedings of Research and Applications in Artificial Intelligence: RAAI …, 2021 | 5 | 2021 |
| Modeling global solar radiation using machine learning with model selection approach: a case study in Tanzania SCA Basílio, RO Silva, CM Saporetti, L Goliatt Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2022 …, 2022 | 3 | 2022 |
| Exploring Quantum-Dot Engineered Solid-State Photon Upconversion in PbS:/CuBiO Using Density Functional Theory and Machine Learning Methods for … DDK Wayo, V Kudryashov, M Karibayev, GE Fynn, K Rafikova, ... arXiv preprint arXiv:2501.00573, 2024 | 1 | 2024 |
| Comparaçao de métodos de agrupamento para classificaçao de dados petrográficos CM Saporetti, JT CEVOLANI, LC de OLIVEIRA, L GOLIATT, E Pereira XI Simpósio de Mecânica Computacional e II Encontro Mineiro de Modelagem …, 2014 | 1 | 2014 |
| Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification T Boratto, GO Costa, A Meireles, AKSTR Alves, CM Saporetti, M Bodini, ... Signals 6 (1), 9, 2025 | | 2025 |
