Matheus Henrique Dal Molin Ribeiro

According to our database, Matheus Henrique Dal Molin Ribeiro authored at least 24 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Electricity Consumption Forecasting: An Approach Using Cooperative Ensemble Learning with SHapley Additive exPlanations.

Eduardo Luiz Alba, Gilson Adamczuk Oliveira, Matheus Henrique Dal Molin Ribeiro, Érick Oliveira Rodrigues

CoRR, May, 2026

Hybrid Kalman Filter-Kolmogorov-Arnold Network Using Local Interpretable Model-Agnostic Explanations for Photovoltaic Power Forecasting.

João Pedro Matos-Carvalho, Stéfano Frizzo Stefenon, Matheus Henrique Dal Molin Ribeiro, Kin Choong Yow

SN Comput. Sci., April, 2026

Wildfire spots analysis and forecasting: Evaluation of univariate and multivariate based on variational mode decomposition models.

Vinicius Lovatel Rocha, Ramon Gomes da Silva, Gilson Adamczuk Oliveira, Matheus Henrique Dal Molin Ribeiro

Appl. Soft Comput., 2026

2025

Enhanced Random Vector Functional Link Networks With Bayesian-Based Hyperparameter Optimization for Wind Speed Forecasting.

Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Matheus Henrique Dal Molin Ribeiro, Stéfano Frizzo Stefenon

IEEE Access, 2025

A Systematic Evaluation of Current Architectures in Wind Power Forecasting.

Vinícius Bortolini, Gilson Adamczuk Oliveira, Érick Oliveira Rodrigues, Matheus Henrique Dal Molin Ribeiro

IEEE Access, 2025

2024

Water and Electricity Consumption Forecasting at an Educational Institution using Machine Learning models with Metaheuristic Optimization.

Eduardo Luiz Alba, Matheus Henrique Dal Molin Ribeiro, Gilson Adamczuk Oliveira, Flavio Trojan, Érick Oliveira Rodrigues

CoRR, 2024

Variational mode decomposition and bagging extreme learning machine with multi-objective optimization for wind power forecasting.

Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Sinvaldo Rodrigues Moreno, Cristiane Canton, José Henrique Kleinübing Larcher, Stéfano Frizzo Stefenon, Viviana Cocco Mariani, Leandro dos Santos Coelho

Appl. Intell., 2024

2023

Decoding Electroencephalography Signal Response by Stacking Ensemble Learning and Adaptive Differential Evolution.

Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, José Henrique Kleinübing Larcher, Andre Mendes, Viviana Cocco Mariani, Leandro dos Santos Coelho

Sensors, August, 2023

2022

Extreme gradient boosting model based on improved Jaya optimizer applied to forecasting energy consumption in residential buildings.

João Guilherme Sauer, Viviana Cocco Mariani, Leandro dos Santos Coelho, Matheus Henrique Dal Molin Ribeiro, Mirco Rampazzo

Evol. Syst., 2022

Discrete differential evolution metaheuristics for permutation flow shop scheduling problems.

Márcia de Fátima Morais, Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Viviana Cocco Mariani, Leandro dos Santos Coelho

Comput. Ind. Eng., 2022

Forecasting the COVID-19 Space-Time Dynamics in Brazil With Convolutional Graph Neural Networks and Transport Modals.

Lucas Caldeira de Oliveira, Jefferson Tales Oliva, Matheus Henrique Dal Molin Ribeiro, Marcelo Teixeira, Dalcimar Casanova

IEEE Access, 2022

Wind power forecasting based on bagging extreme learning machine ensemble model.

Matheus Henrique Dal Molin Ribeiro, Sinvaldo Rodrigues Moreno, Ramon Gomes da Silva, José Henrique Kleinübing Larcher, Cristiane Canton, Viviana Cocco Mariani, Leandro dos Santos Coelho

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting.

Stéfano Frizzo Stefenon, Matheus Henrique Dal Molin Ribeiro, Ademir Nied, Viviana Cocco Mariani, Leandro dos Santos Coelho, Valderi Reis Quietinho Leithardt, Luis Augusto Silva, Laio Oriel Seman

IEEE Access, 2021

Seasonal-trend and multiobjective ensemble learning model for water consumption forecasting.

Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, José Henrique Kleinübing Larcher, José Donizetti de Lima, Viviana Cocco Mariani, Leandro dos Santos Coelho

Proceedings of the International Joint Conference on Neural Networks, 2021

Forecasting COVID-19 pandemic using an echo state neural network-based framework.

José Henrique Kleinübing Larcher, Ramon Gomes da Silva, Matheus Henrique Dal Molin Ribeiro, Leandro dos Santos Coelho, Viviana Cocco Mariani

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Multi-step ahead meningitis case forecasting based on decomposition and multi-objective optimization methods.

Matheus Henrique Dal Molin Ribeiro, Viviana Cocco Mariani, Leandro dos Santos Coelho

J. Biomed. Informatics, 2020

Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil.

Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Viviana Cocco Mariani, Leandro dos Santos Coelho

CoRR, 2020

Forecasting Brazilian and American COVID-19 cases based on artificial intelligence coupled with climatic exogenous variables.

Ramon Gomes da Silva, Matheus Henrique Dal Molin Ribeiro, Viviana Cocco Mariani, Leandro dos Santos Coelho

CoRR, 2020

Short-term forecasting of Amazon rainforest fires based on ensemble decomposition model.

Ramon Gomes da Silva, Matheus Henrique Dal Molin Ribeiro, Viviana Cocco Mariani, Leandro dos Santos Coelho

CoRR, 2020

Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series.

Matheus Henrique Dal Molin Ribeiro, Leandro dos Santos Coelho

Appl. Soft Comput., 2020

Multi-step ahead Bitcoin Price Forecasting Based on VMD and Ensemble Learning Methods.

Ramon Gomes da Silva, Matheus Henrique Dal Molin Ribeiro, Naylene Fraccanabbia, Viviana Cocco Mariani, Leandro dos Santos Coelho

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Electricity energy price forecasting based on hybrid multi-stage heterogeneous ensemble: Brazilian commercial and residential cases.

Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Cristiane Canton, Naylene Fraccanabbia, Viviana Cocco Mariani, Leandro dos Santos Coelho

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Solar Power Forecasting Based on Ensemble Learning Methods.

Naylene Fraccanabbia, Ramon Gomes da Silva, Matheus Henrique Dal Molin Ribeiro, Sinvaldo Rodrigues Moreno, Leandro dos Santos Coelho, Viviana Cocco Mariani

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Multi-Objective Ensemble Model for Short-Term Price Forecasting in Corn Price Time Series.

Matheus Henrique Dal Molin Ribeiro, Victor Henrique Alves Ribeiro, Gilberto Reynoso-Meza, Leandro dos Santos Coelho

Proceedings of the International Joint Conference on Neural Networks, 2019