Improving the accuracy of intelligent forecasting models using the Perturbation Theory. - Eraylson G. Silva; Domingos S. de O. Junior; George D. C. Cavalcanti; Paulo S. G. de Mattos Neto (IJCNN, 2018)

Hybrid System for Time Series using Iterative Residual Forecasting Models. - Eraylson Galdino da Silva; Paulo Salgado Gomes de Mattos Neto; João Fausto Lorenzato de Oliveira (BRACIS, 2019)

Exceptional Survival Model Mining. - Juliana Barcellos Mattos; Eraylson G. Silva; Paulo S. G. de Mattos Neto; Renato Vimieiro (BRACIS (2), 2020)

On the evaluation of dynamic selection parameters for time series forecasting. - Eraylson G. Silva; George D. C. Cavalcanti; João Fausto Lorenzato de Oliveira; Paulo S. G. de Mattos Neto (IJCNN, 2020)

A temporal-window framework for modelling and forecasting time series. - Paulo S. G. de Mattos Neto; George D. C. Cavalcanti; Paulo Renato A. Firmino; Eraylson G. Silva; Sérgio R. P. Vila Nova Filho (Knowl. Based Syst., 2020)

A Dynamic Predictor Selection Method Based on Recent Temporal Windows for Time Series Forecasting. - Eraylson G. Silva; Paulo S. G. de Mattos Neto; George D. C. Cavalcanti (IEEE Access, 2021)

A Hybrid System Based on Dynamic Selection for Time Series Forecasting. - João F. L. de Oliveira; Eraylson G. Silva; Paulo S. G. de Mattos Neto (IEEE Trans. Neural Networks Learn. Syst., 2022)

Time series univariate. - Eraylson Galdino da Silva (IEEE DataPort, 2022)

Enhancing Text Recognition in OCR Systems Through Image Processing with BSRGAN. - Fernando Baptistella de Lima; Eraylson Galdino da Silva (SBSI, 2025)