| 1 |
Wind turbine power curve modeling based on Gaussian Processes and Artificial Neural Networks
Manobel B, Sehnke F, Lazzus JA, Salfate I, Felder M, Montecinos S
Renewable Energy, 125, 1015, 2018 |
| 2 |
Estimating the Temperature-Dependent Surface Tension of Ionic Liquids Using a Neural Network-Based Group Contribution Method
Lazzus JA, Cuturrufo F, Pulgar-Villarroel G, Salfate I, Vega P
Industrial & Engineering Chemistry Research, 56(23), 6869, 2017 |
| 3 |
A group contribution method to predict the thermal conductivity lambda(T,P) of ionic liquids
Lazzus JA
Fluid Phase Equilibria, 405, 141, 2015 |
| 4 |
A group contribution method to predict the melting point of ionic liquids
Lazzus JA
Fluid Phase Equilibria, 313, 1, 2012 |
| 5 |
Application of particle swarm optimization to model the phase equilibrium of complex mixtures
Lazzus JA, Ponce AAP, Chilla LOP
Fluid Phase Equilibria, 317, 132, 2012 |
| 6 |
A group contribution method to predict the glass transition temperature of ionic liquids
Lazzus JA
Thermochimica Acta, 528, 38, 2012 |
| 7 |
Neural network/particle swarm method to predict flammability limits in air of organic compounds
Lazzus JA
Thermochimica Acta, 512(1-2), 150, 2011 |
| 8 |
A GROUP CONTRIBUTION METHOD TO PREDICT -T-P OF IONIC LIQUIDS
Lazzus JA
Chemical Engineering Communications, 197(7), 974, 2010 |
| 9 |
Prediction of Flash Point Temperature of Organic Compounds Using a Hybrid Method of Group Contribution plus Neural Network plus Particle Swarm Optimization
Lazzus JA
Chinese Journal of Chemical Engineering, 18(5), 817, 2010 |
| 10 |
Estimation of solid vapor pressures of pure compounds at different temperatures using a multilayer network with particle swarm algorithm
Lazzus JA
Fluid Phase Equilibria, 289(2), 176, 2010 |
