Indonesian electricity load forecasting using singular spectrum analysis, fuzzy systems and neural networks W Sulandari, MH Lee, PC Rodrigues Energy 190, 116408, 2020 | 77 | 2020 |
A Weighted AMMI Algorithm to Study Genotype-by-Environment Interaction and QTL-by-Environment Interaction PC Rodrigues, M Malosetti, HG Gauch, FA van Eeuwijk Crop Science 54, 1555-1570, 2014 | 65 | 2014 |
Tracking the US business cycle with a singular spectrum analysis M De Carvalho, PC Rodrigues, A Rua Economics Letters, 2011 | 63 | 2011 |
A robust AMMI model for the analysis of genotype-by-environment data PC Rodrigues, A Monteiro, VM Lourenço Bioinformatics 32 (1), 58-66, 2016 | 56 | 2016 |
Air quality assessment and pollution forecasting using artificial neural networks in Metropolitan Lima-Peru CH Cordova, MNL Portocarrero, R Salas, R Torres, PC Rodrigues, ... Scientific Reports 11 (1), 24232, 2021 | 50 | 2021 |
Two New Strategies for Detecting and Understanding QTL× Environment Interactions HG GAUCH, PC Rodrigues, JD Munkvold, EL Heffner, M Sorrells Crop science 51 (1), 96-113, 2011 | 49 | 2011 |
The benefits of multivariate singular spectrum analysis over the univariate version PC Rodrigues, R Mahmoudvand Journal of the Franklin Institute 355 (1), 544-564, 2018 | 43 | 2018 |
Adaptation of Winter Wheat Cultivars to Different Environments: A Case Study in Poland M Iwańska, J Paderewski, M Stępień, PC Rodrigues Agronomy 10 (5), 632, 2020 | 42 | 2020 |
Missing value imputation in time series using Singular Spectrum Analysis R Mahmoudvand, PC Rodrigues International Journal of Energy and Statistics 4 (01), 1650005, 2016 | 41 | 2016 |
Genetic and QTL analyses of yield and a set of physiological traits in pepper NA Alimi, M Bink, JA Dieleman, M Nicolaï, M Wubs, E Heuvelink, J Magan, ... Euphytica 190 (2), 181-201, 2013 | 41 | 2013 |
Statistical and Artificial Neural Networks Models for Electricity Consumption Forecasting in the Brazilian Industrial Sector F Leite Coelho da Silva, K da Costa, P Canas Rodrigues, R Salas, ... Energies 15 (2), 588, 2022 | 40 | 2022 |
Neural Networks for Financial Time Series Forecasting K Sako, BN Mpinda, PC Rodrigues Entropy 24 (5), 657, 2022 | 39 | 2022 |
The usefulness of EM-AMMI to study the influence of missing data pattern and application to Polish post-registration winter wheat data J Paderewski, PC Rodrigues Australian Journal of Crop Science 8 (4), 2014 | 38 | 2014 |
Exponential Smoothing on Modeling and Forecasting Multiple Seasonal Time Series: An Overview W Sulandari, Suhartono, Subanar, PC Rodrigues Fluctuation and Noise Letters 20 (04), 2130003, 2021 | 37 | 2021 |
Spectral modeling of time series with missing data PC Rodrigues, M De Carvalho Applied Mathematical Modelling 37 (7), 4676-4684, 2013 | 36 | 2013 |
A comparison between joint regression analysis and the additive main and multiplicative interaction model: the robustness with increasing amounts of missing data PC Rodrigues, DGS Pereira, JT Mexia Scientia Agricola 68 (6), 679-686, 2011 | 36* | 2011 |
A new parsimonious recurrent forecasting model in singular spectrum analysis R Mahmoudvand, PC Rodrigues Journal of Forecasting, 2017 | 29 | 2017 |
Yield response of winter wheat to agro-ecological conditions using additive main effects and multiplicative interaction and cluster analysis J Paderewski, HG Gauch, W Mądry, T Drzazga, PC Rodrigues Crop Science 51 (3), 969-980, 2011 | 29 | 2011 |
Time series forecasting using singular spectrum analysis, fuzzy systems and neural networks W Sulandari, S Subanar, MH Lee, PC Rodrigues MethodsX, 101015, 2020 | 27 | 2020 |
Forecasting mortality rate by multivariate singular spectrum analysis R Mahmoudvand, D Konstantinides, PC Rodrigues Applied Stochastic Models in Business and Industry, 2017 | 27 | 2017 |