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ORCIDLeonardo Goliatt da Fonseca
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2020 – today
- 2024
[j19]Hai Tao, Sani Isah Abba
, Ahmed M. Al-Areeq, Fredolin Tangang, Sandeep Samantaray, Abinash Sahoo, Hugo Valadares Siqueira, Saman Maroufpoor, Vahdettin Demir, Neeraj Dhanraj Bokde, Leonardo Goliatt, Mehdi Jamei, Iman Ahmadianfar, Suraj Kumar Bhagat, Bijay Halder, Tianli Guo, Daniel S. Helman, Mumtaz Ali, Sabaa Sattar, Zainab Al-Khafaji, Shamsuddin Shahid, Zaher Mundher Yaseen:
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions. Eng. Appl. Artif. Intell. 129: 107559 (2024)- [j18]Hai Tao, Zainab Hasan Ali, Faisal M. Mukhtar, Ahmed W. Al Zand, Haydar Abdulameer Marhoon, Leonardo Goliatt, Zaher Mundher Yaseen:
Coupled extreme gradient boosting algorithm with artificial intelligence models for predicting compressive strength of fiber reinforced polymer- confined concrete. Eng. Appl. Artif. Intell. 134: 108674 (2024) - [j17]Davi Gotardelo, Leonardo Goliatt:
Multi-objective optimization of portfolio selection involving non-convex attributes in an anti-fragile perspective. Evol. Syst. 15(3): 703-715 (2024) - [j16]Tales H. A. Boratto, Camila Martins Saporetti, Samuel da Costa Alves Basilio, Alexandre A. Cury, Leonardo Goliatt:
Data-driven cymbal bronze alloy identification via evolutionary machine learning with automatic feature selection. J. Intell. Manuf. 35(1): 257-273 (2024) - [j15]Suraj Kumar Bhagat, Tiyasha Tiyasha, A. H. Shather, Mehdi Jamei, Adarsh Kumar, Zainab Al-Khafaji, Leonardo Goliatt, Shafik S. Shafik, Omer A. Alawi, Zaher Mundher Yaseen:
Wind speed prediction and insight for generalized predictive modeling framework: a comparative study for different artificial intelligence models. Neural Comput. Appl. 36(23): 14119-14150 (2024) - 2023
- [j14]Samuel da Costa Alves Basilio, Fernando Ferrari Putti, Angélica Carvalho Cunha, Leonardo Goliatt:
An evolutionary-assisted machine learning model for global solar radiation prediction in Minas Gerais region, southeastern Brazil. Earth Sci. Informatics 16(3): 2049-2067 (2023) - [j13]Leonardo Goliatt, Zaher Mundher Yaseen:
Development of a hybrid computational intelligent model for daily global solar radiation prediction. Expert Syst. Appl. 212: 118295 (2023) - [j12]Tales H. A. Boratto, Alexandre A. Cury, Leonardo Goliatt:
Machine learning-based classification of bronze alloy cymbals from microphone captured data enhanced with feature selection approaches. Expert Syst. Appl. 215: 119378 (2023) - [j11]Carolina Ribeiro Xavier, João Gabriel Rocha Silva, Grasiele Regina Duarte, Iago Augusto de Carvalho, Vinícius da Fonseca Vieira, Leonardo Goliatt:
An island-based hybrid evolutionary algorithm for caloric-restricted diets. Evol. Intell. 16(2): 553-564 (2023) - [j10]Victor Rezende Franco, Marcos Cicarini Hott, Ricardo Guimarães Andrade, Leonardo Goliatt:
Hybrid machine learning methods combined with computer vision approaches to estimate biophysical parameters of pastures. Evol. Intell. 16(4): 1271-1284 (2023) - [j9]Samuel da Costa Alves Basilio, Camila Martins Saporetti, Leonardo Goliatt:
An interdependent evolutionary machine learning model applied to global horizontal irradiance modeling. Neural Comput. Appl. 35(16): 12099-12120 (2023) - [j8]Rodrigo Oliveira Silva, Camila Martins Saporetti, Zaher Mundher Yaseen, Egberto Pereira, Leonardo Goliatt:
An approach for total organic carbon prediction using convolutional neural networks optimized by differential evolution. Neural Comput. Appl. 35(28): 20803-20817 (2023) - 2022
- [j7]Michell Hell, Eduardo Pestana de Aguiar, Nielson Soares, Leonardo Goliatt:
A Data-Driven Time-Series Fault Prediction Framework for Dynamically Evolving Large-Scale Data Streaming Systems. Int. J. Fuzzy Syst. 24(6): 2831-2844 (2022) - 2021
- [j6]Camila Martins Saporetti, Leonardo Goliatt, Egberto Pereira:
Neural network boosted with differential evolution for lithology identification based on well logs information. Earth Sci. Informatics 14(1): 133-140 (2021) - [j5]Nielson Soares, Eduardo Pestana de Aguiar, Amanda Campos Souza, Leonardo Goliatt:
Unsupervised machine learning techniques to prevent faults in railroad switch machines. Int. J. Crit. Infrastructure Prot. 33: 100423 (2021) - [j4]Grasiele Regina Duarte, Afonso Celso de Castro Lemonge, Leonardo Goliatt da Fonseca, Beatriz Souza Leite Pires de Lima:
An Island Model based on Stigmergy to solve optimization problems. Nat. Comput. 20(3): 413-441 (2021) - [c27]Gabriel Dias de Abreu, Letícia Florentino Pires, Luciana Conceição Dias Campos, Leonardo Goliatt:
Multitask Learning for Predicting Natural Flows: A Case Study at Paraiba do Sul River. EPIA 2021: 163-175 - [c26]Gisele Goulart Tavares, Priscila V. S. Z. Capriles, Leonardo Goliatt:
Automatic Evolutionary Settings of Machine Learning Methods for Buildings' Thermal Loads Prediction. EPIA 2021: 183-195 - [c25]Igor Michel Santos Leite, João Daniel Madureira Yamim, Leonardo Goliatt da Fonseca:
The DeepONets for Finance: An Approach to Calibrate the Heston Model. EPIA 2021: 351-362 - 2020
- [c24]Rodrigo C. A. F. Pontes, Grasiele Regina Duarte, Leonardo Goliatt:
Migration Guided by a Performance Index in Heterogeneous Island Models. BIOMA 2020: 125-134 - [c23]Alfeu D. Martinho, Celso B. M. Ribeiro, Yulia Gorodetskaya, Tales L. Fonseca, Leonardo Goliatt:
Extreme Learning Machine with Evolutionary Parameter Tuning Applied to Forecast the Daily Natural Flow at Cahora Bassa Dam, Mozambique. BIOMA 2020: 255-267 - [c22]Tales L. Fonseca, Leonardo Goliatt:
Hybrid Extreme Learning Machine and Backpropagation with Adaptive Activation Functions for Classification Problems. ISDA 2020: 19-29 - [c21]João P. Scoralick, Gabriele C. Iwashima, Fernando Antonio Basile Colugnati, Leonardo Goliatt, Priscila V. S. Z. Capriles:
A Extreme Gradient Boosting Classifier for Predicting Chronic Kidney Disease Stages. ISDA 2020: 901-910 - [c20]Alfeu D. Martinho, Tales L. Fonseca, Leonardo Goliatt:
Automated Extreme Learning Machine to Forecast the Monthly Flows: A Case Study at Zambezi River. ISDA 2020: 1314-1324
2010 – 2019
- 2019
- [j3]Camila Martins Saporetti, Leonardo Goliatt da Fonseca, Egberto Pereira:
A Lithology Identification Approach Based on Machine Learning With Evolutionary Parameter Tuning. IEEE Geosci. Remote. Sens. Lett. 16(12): 1819-1823 (2019) - [c19]Leonardo Goliatt, Priscila V. S. Z. Capriles, Gisele Goulart Tavares:
Gradient Boosting Ensembles for Predicting Heating and Cooling Loads in Building Design. EPIA (1) 2019: 495-506 - [c18]Luciana Conceição Dias Campos, Leonardo Goliatt da Fonseca, Tales L. Fonseca, Gabriel Dias de Abreu, Letícia Florentino Pires, Yulia Gorodetskaya:
Short-Term Streamflow Forecasting for Paraíba do Sul River Using Deep Learning. EPIA (1) 2019: 507-518 - [c17]Vinicius Carius de Souza, Leonardo Goliatt, Priscila V. S. Z. Capriles:
Insight About Nonlinear Dimensionality Reduction Methods Applied to Protein Molecular Dynamics. IWBBIO (2) 2019: 219-230 - 2018
- [j2]Camila Martins Saporetti, Grasiele Regina Duarte, Tales L. Fonseca, Leonardo Goliatt da Fonseca, Egberto Pereira:
Extreme Learning Machine combined with a Differential Evolution algorithm for lithology identification. RITA 25(4): 43-56 (2018) - [c16]Grasiele Regina Duarte, Afonso C. C. Lemonge, Leonardo Goliatt da Fonseca:
A New Strategy to Evaluate the Attractiveness in a Dynamic Island Model. CEC 2018: 1-8 - [c15]Leonardo Goliatt da Fonseca, Priscila V. S. Z. Capriles, Grasiele Regina Duarte:
Modeling Heating and Cooling Loads in Buildings Using Gaussian Processes. CEC 2018: 1-6 - [c14]Leonardo Goliatt da Fonseca, Michèle Cristina Resende Farage:
An Extreme Learning Machine with Feature Selection for Estimating Mechanical Properties of Lightweight Aggregate Concretes. CEC 2018: 1-7 - [c13]Rafaela Abreu Campos, Renan Piazzaroli Finotti Amaral, Ivan Fabio Mota de Menezes, Leonardo Goliatt da Fonseca, Moises Luiz Lagares, Eduardo Pestana de Aguiar:
Classification of Short Circuit GMA Welding using Type-1 and Singleton Fuzzy Logic System. FUZZ-IEEE 2018: 1-7 - 2017
- [c12]Grasiele Regina Duarte, Afonso C. C. Lemonge, Leonardo Goliatt da Fonseca:
A dynamic migration policy to the Island Model. CEC 2017: 1135-1142 - [c11]João Gabriel Rocha Silva, Iago Augusto de Carvalho, Leonardo Goliatt, Vinícius da Fonseca Vieira, Carolina Ribeiro Xavier:
A Differential Evolution Algorithm for Computing Caloric-Restricted Diets - Island-Based Model. ICCSA (1) 2017: 385-400 - [c10]Rodrigo Barbosa de Santis, Eduardo Pestana de Aguiar, Leonardo Goliatt da Fonseca:
Predicting material backorders in inventory management using machine learning. LA-CCI 2017: 1-6 - [c9]Vinicius Carius de Souza, Leonardo Goliatt, Priscila V. Z. Capriles Goliatt:
Clustering algorithms applied on analysis of protein molecular dynamics. LA-CCI 2017: 1-6 - 2016
- [c8]Tales L. Fonseca, Leonardo Goliatt, Luciana Conceição Dias Campos, Flávia de Souza Bastos, Luis Paulo S. Barra, Rodrigo Weber dos Santos:
Machine Learning Approaches to Estimate Simulated Cardiac Ejection Fraction from Electrical Impedance Tomography. IBERAMIA 2016: 235-246 - 2012
- [c7]Leonardo Goliatt da Fonseca, Afonso C. C. Lemonge, Helio J. C. Barbosa:
A study on fitness inheritance for enhanced efficiency in real-coded genetic algorithms. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c6]Leonardo Goliatt da Fonseca, Heder S. Bernardino, Helio J. C. Barbosa:
A Genetic Algorithm Assisted by a Locally Weighted Regression Surrogate Model. ICCSA (1) 2012: 125-135 - 2011
- [j1]Heder S. Bernardino, Helio J. C. Barbosa, Leonardo Goliatt da Fonseca:
Surrogate-assisted clonal selection algorithms for expensive optimization problems. Evol. Intell. 4(2): 81-97 (2011) - 2010
- [b1]Leonardo Goliatt da Fonseca:
Genetic algorithms assisted by similarity-based metamodels. Laboratório Nacional de Computação Científica, Brazil, 2010 - [c5]Heder S. Bernardino, Helio J. C. Barbosa, Leonardo Goliatt da Fonseca:
A Faster Clonal Selection Algorithm for Expensive Optimization Problems. ICARIS 2010: 130-143 - [c4]Helio J. C. Barbosa, Afonso C. C. Lemonge, Leonardo Goliatt da Fonseca, Heder S. Bernardino:
Comparing Two Constraint Handling Techniques in a Binary-Coded Genetic Algorithm for Optimization Problems. SEAL 2010: 125-134
2000 – 2009
- 2009
- [c3]Leonardo Goliatt da Fonseca, Helio J. C. Barbosa, Afonso C. C. Lemonge:
A similarity-based surrogate model for expensive evolutionary optimization with fixed budget of simulations. IEEE Congress on Evolutionary Computation 2009: 867-874 - 2008
- [c2]Heder S. Bernardino, Helio J. C. Barbosa, Afonso C. C. Lemonge, Leonardo Goliatt da Fonseca:
A new hybrid AIS-GA for constrained optimization problems in mechanical engineering. IEEE Congress on Evolutionary Computation 2008: 1455-1462 - 2007
- [c1]Leonardo Goliatt da Fonseca, Priscila V. S. Z. Capriles, Helio J. C. Barbosa, Afonso C. C. Lemonge:
A Stochastic Rank-Based Ant System for Discrete Structural Optimization. SIS 2007: 68-75
Coauthor Index
aka: Priscila V. Z. Capriles Goliatt
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last updated on 2024-10-07 22:06 CEST by the dblp team
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