High-resolution prediction of quenching behavior using machine learning based on optical fiber temperature measurement

This publication has 46 references indexed in Scilit:

• Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
  PLOS ONE, 2013
• CATHARE 2 V2.5_2: A single version for various applications
  Nuclear Engineering and Design, 2011
• Analysis of CHF in saturated forced convective boiling on a heated surface with impinging jets using artificial neural network and genetic algorithm
  Nuclear Engineering and Design, 2011
• Primal and dual model representations in kernel-based learning
  Statistics Surveys, 2010
• The Support Vector Regression with the parameter tuning assisted by a differential evolution technique: Study of the critical velocity of a slurry flow in a pipeline
  Chemical Industry and Chemical Engineering Quarterly, 2008
• Modeling flow boiling heat transfer of pure fluids through artificial neural networks
  International Journal of Thermal Sciences, 2006
• A look-up table for fully developed film-boiling heat transfer
  Nuclear Engineering and Design, 2003
• EFFECTS OF SURFACE ROUGHNESS, OXIDATION LEVEL, AND LIQUID SUBCOOLING ON THE MINIMUM FILM BOILING TEMPERATURE
  Experimental Heat Transfer, 2003
• Parametric trends analysis of the critical heat flux based on artificial neural networks
  Nuclear Engineering and Design, 1996
• Film-Boiling Heat Transfer From a Horizontal Surface
  Journal of Heat Transfer, 1961