High Fidelity Approximation of Slow Simulators Using Machine Learning for Real-time Simulation/Optimization

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Sudip Regmi and Larry M. Deschaine and 
                 Sharad R. Regmi",
  title =        "High Fidelity Approximation of Slow Simulators Using
                 Machine Learning for Real-time
  booktitle =    "2004 Business and Industry Symposium",
  year =         "2004",
  address =      "Arlington, Virginia, USA",
  month =        "18-22 " # apr,
  organisation = "Society for Modeling and Simulation International",
  keywords =     "genetic algorithms, genetic programming, Simulation,
                 Machine Learning, Optimisation",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/deschaine/ASTC_2004_KodakMachLearnComparision.pdf",
  broken =       "http://www.scs.org/getDoc.cfm?id=1707",
  broken =       "http://www.scs.org/docInfo.cfm?get=1707",
  size =         "6 pages",
  abstract =     "Simulation and optimisation of industrial processes is
                 cost effective and profit productive. Often, high
                 fidelity models require extensive resources to code and
                 require long execution times. In this work, we examine
                 using machine learning techniques to replace simulation
                 models with high fidelity approximations. We test
                 linear genetic programming, linear regression, and
                 machine learning paradigms. The results show that high
                 fidelity approximations (R2 of 0.99) are possible that
                 execute in a fraction of the time required by the
                 original simulator. These solutions are coded into web
                 services so that a plant manager can input standard
                 information into a user friendly web page, but produce
                 results in a few milliseconds as opposed to hours. This
                 advantage allows for real-time dynamic planning and
                 optimization on the plant floor.",
  notes =        "



Genetic Programming entries for Sudip Regmi Larry M Deschaine Sharad R Regmi