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Leonardo Goliatt

Observed names: Goliatt, Leonardo, L. GOLIATT, L. Goliatt, L. Goliatt da Fonseca, Leonardo G., Leonardo G. Fonseca, Leonardo G. da Fonseca, Leonardo Goliatt Da Fonseca, Leonardo Goliatt da Fonseca, Leonardo Golliat
ORCID: 0000-0002-2844-9470
Observed ORCID: 0000-0002-2844-9470
OpenAlex ID: A5004862221
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
2023 · Hai Tao, Sani I. Abba, et al. · Engineering Applications of Artificial Intelligence · 142
A Lithology Identification Approach Based on Machine Learning With Evolutionary Parameter Tuning
2019 · Camila Martins Saporetti, Leonardo Goliatt da Fonseca, et al. · IEEE Geoscience and Remote Sensing Letters · 95
Machine learning-based country-level annual air pollutants exploration using Sentinel-5P and Google Earth Engine
2023 · Bijay Halder, Iman Ahmadianfar, et al. · Scientific Reports · 77
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Machine learning approaches for petrographic classification of carbonate-siliciclastic rocks using well logs and textural information
2018 · Camila Martins Saporetti, Leonardo Goliatt da Fonseca, et al. · Journal of Applied Geophysics · 75
Development of a hybrid computational intelligent model for daily global solar radiation prediction
2022 · Leonardo Goliatt, Zaher Mundher Yaseen · Expert Systems with Applications · 73
Rank‐based ant colony algorithms for truss weight minimization with discrete variables
2006 · Priscila V. S. Z. Capriles, Leonardo G. Fonseca, et al. · Communications in Numerical Methods in Engineering · 60
Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields
2022 · C.M. Saporetti, D.L. Fonseca, et al. · Marine and Petroleum Geology · 51
Neural network boosted with differential evolution for lithology identification based on well logs information
2020 · Camila Martins Saporetti, Leonardo Goliatt, et al. · Earth Science Informatics · 42
Super learner approach to predict total organic carbon using stacking machine learning models based on well logs
2023 · L. Goliatt, C.M. Saporetti, et al. · Fuel · 40
Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields
2023 · Leonardo Goliatt, C.M. Saporetti, et al. · Petroleum · 38
Gradient Boosting Hybridized with Exponential Natural Evolution Strategies for Estimating the Strength of Geopolymer Self-Compacting Concrete
2022 · Samuel Alves Basilio, Leonardo Goliatt · Knowledge-Based Engineering and Sciences · 38
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Predicting material backorders in inventory management using machine learning
2017 · Rodrigo Barbosa de Santis, Eduardo Pestana de Aguiar, et al. · IEEE Latin American Conference on Computational Intelligence (LA-CCI) · 36
Covariance Matrix Adaptation Evolution Strategy for Improving Machine Learning Approaches in Streamflow Prediction
2022 · Rana Muhammad Adnan Ikram, Leonardo Goliatt, et al. · Mathematics · 35
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Coupled extreme gradient boosting algorithm with artificial intelligence models for predicting compressive strength of fiber reinforced polymer- confined concrete
2024 · Hai Tao, Zainab Hasan Ali, et al. · Engineering Applications of Artificial Intelligence · 32
Uma comparação de técnicas de aprendizado de máquina para a previsão de cargas energéticas em edifícios
2017 · Grasiele Regina Duarte, Leonardo Goliatt da Fonseca, et al. · Ambiente Construído · 32
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Short-term streamflow modeling using data-intelligence evolutionary machine learning models
2023 · Alfeu D. Martinho, Henrique S. Hippert, et al. · Scientific Reports · 30
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Approaches for the short-term prediction of natural daily streamflows using hybrid machine learning enhanced with grey wolf optimization
2022 · Alfeu D. Martinho, Camila M. Saporetti, et al. · Hydrological Sciences Journal · 29
Development of hybrid computational data-intelligence model for flowing bottom-hole pressure of oil wells: New strategy for oil reservoir management and monitoring
2023 · Leonardo Goliatt, Reem Sabah Mohammad, et al. · Fuel · 27
Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm
2024 · Zaher Mundher Yaseen, Wan Hanna Melini Wan Mohtar, et al. · Chemosphere · 26
Extreme Learning Machine combined with a Differential Evolution algorithm for lithology identification
2018 · Camila Martins Saporetti, Grasiele Regina Duarte, et al. · Revista de Informática Teórica e Aplicada · 26
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Evolutionary automated radial basis function neural network for multiphase flowing bottom-hole pressure prediction
2024 · Deivid Campos, Dennis Delali Kwesi Wayo, et al. · Fuel · 25
Hybrid particle swarm optimization and group method of data handling for short-term prediction of natural daily streamflows
2022 · Danilo P. M. Souza, Alfeu D. Martinho, et al. · Modeling Earth Systems and Environment · 25
Data driven insights for parabolic trough solar collectors: Artificial intelligence-based energy and exergy performance analysis
2024 · Hai Tao, Omer A. Alawi, et al. · Journal of Cleaner Production · 24
Multi-criteria supplier selection using fuzzy analytic hierarchy process: case study from a Brazilian railway operator
2017 · Rodrigo Barbosa de Santis, Leonardo Golliat, et al. · Brazilian Journal of Operations & Production Management · 23
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Unsupervised machine learning techniques to prevent faults in railroad switch machines
2021 · Nielson Soares, Eduardo Pestana de Aguiar, et al. · International Journal of Critical Infrastructure Protection · 22
Works count: 210
Citation count: 1,945
H-index: 23
I10-index: 62
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