Performance comparison of artificial neural networks and expert systems applied to flow pattern identification in vertical ascendant gas–liquid flows ES Rosa, RM Salgado, T Ohishi, N Mastelari International Journal of Multiphase Flow 36 (9), 738-754, 2010 | 165 | 2010 |
A hybrid ensemble model applied to the short-term load forecasting problem RM Salgado, JJF Pereira, T Ohishi, R Ballini, CAM Lima, FJ Von Zuben The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 28 | 2006 |
A short-term bus load forecasting system RM Salgado, T Ohishi, R Ballini 2010 10th International Conference on Hybrid Intelligent Systems, 55-60, 2010 | 23 | 2010 |
A hybrid approach to the load forecasting based on decision trees RM Salgado, RR Lemes Journal of Control, Automation and Electrical Systems 24, 854-862, 2013 | 17 | 2013 |
An hybrid aggregate model applied to the short-term bus load forecasting problem RM Salgado, R Ballini, T Ohishi 2009 IEEE Bucharest PowerTech, 1-8, 2009 | 14 | 2009 |
Clustering bus load curves RS Salgado, T Ohishi, R Ballini IEEE PES Power Systems Conference and Exposition, 2004., 1251-1256, 2004 | 13 | 2004 |
An empirical analysis of MLP neural networks applied to streamflow forecasting R Menezes IEEE Latin America Transactions 9 (3), 295-301, 2011 | 11 | 2011 |
An intelligent decision support system to investment in the stock market JA Macedo, LTO Camargo, HCB de Oliveira, LE da Silva, RM Salgado IEEE Latin America Transactions 11 (2), 812-819, 2013 | 9 | 2013 |
Intelligent models to identification and treatment of outliers in electrical load data RM Salgado, TC Machado, T Ohishi IEEE Latin America Transactions 14 (10), 4279-4286, 2016 | 7 | 2016 |
Controle de inércia não monotônico na otimização por enxame de partículas. T Silveira, HCB de Oliveira, LE da Silva, RM Salgado Scientia 20 (2), 2009 | 7 | 2009 |
IoT applied to environmental monitoring in oysters' farms V Viegas, JMD Pereira, P Girão, O Postolache, R Salgado 2018 International Symposium in Sensing and Instrumentation in IoT Era (ISSI …, 2018 | 6 | 2018 |
Modelos de inteligência computacional para geração de séries sintéticas de vazões médias mensais RM Salgado, I Luna, R Ballini, S Soares, D da Silva Filho Learning and Nonlinear Models 10 (3), 166-174, 2012 | 6 | 2012 |
Short-term load forecasting using support vector machines JJF Pereira, RM Salgado, T Ohishi, R Ballini IEEE PES Transmission and Distribution Conference, 2006 | 6 | 2006 |
Very short-term bus reactive load forecasting models based on KDD approach EF Franco, T Ohishi, RM Salgado 2017 IEEE 7th International Conference on Power and Energy Systems (ICPES …, 2017 | 5 | 2017 |
Expert system for dam assessment and emergency detection M Leone-Filho, DAF Balbi, AE Toscano, PSF Barbosa, RM Salgado, ... 6th International conference on flood management, 2014 | 5 | 2014 |
Sistema de suporte á decisão para análise e previsão de carga por barramento RM Salgado Universidade Estadual de Campinas, 2009 | 5 | 2009 |
Hybrid optical fiber sensor and artificial neural network system for bioethanol quality control and productivity enhancement E Gusken, RM Salgado, CEV Rossell, T Ohishi, CK Suzuki 19th International Conference on Optical Fibre Sensors 7004, 437-440, 2008 | 4 | 2008 |
Voltammetry based automated instrument for in-situ and online measurement of heavy metals concentration in water JMD Pereira, O Postolache, R Salgado, PS Girão 1st IMEKO TC19 Symposium on Measurement and Instrumentation for …, 2007 | 4 | 2007 |
Machine learning methods for the prediction of milk fatty acid content J Petrini, RM Salgado, MAP Rodriguez, PF Machado, GB Mourao International Journal of Dairy Technology 75 (3), 553-562, 2022 | 3 | 2022 |
Analysis of two-phase flow pattern identification methodologies for embedded systems EF Franco, RM Salgado, T Ohishi, ES Rosa, N Mastelari IEEE Latin America Transactions 16 (3), 718-727, 2018 | 3 | 2018 |