Evolutionary Data Mining of Digital Logic and the Effects of Uncertainty

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "James F. {Smith III}",
  title =        "Evolutionary Data Mining of Digital Logic and the
                 Effects of Uncertainty",
  booktitle =    "2007 IEEE Congress on Evolutionary Computation",
  year =         "2007",
  editor =       "Dipti Srinivasan and Lipo Wang",
  pages =        "39--46",
  address =      "Singapore",
  month =        "25-28 " # sep,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  ISBN =         "1-4244-1340-0",
  file =         "1179.pdf",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2007.4424452",
  abstract =     "A data mining based procedure for automated reverse
                 engineering has been developed. The data mining
                 algorithm for reverse engineering uses a genetic
                 program (GP) as a data mining function. A genetic
                 program is an algorithm based on the theory of
                 evolution that automatically evolves populations of
                 computer programs or mathematical expressions,
                 eventually selecting one that is optimal in the sense
                 it maximises a measure of effectiveness, referred to as
                 a fitness function. The system to be reverse engineered
                 is typically a sensor. Design documents for the sensor
                 are not available and conditions prevent the sensor
                 from being taken apart. The sensor is used to create a
                 database of input signals and output measurements.
                 Rules about the likely design properties of the sensor
                 are collected from experts. The rules are used to
                 create a fitness function for the genetic program.
                 Genetic program based data mining is then conducted.
                 This procedure incorporates not only the experts' rules
                 into the fitness function, but also the information in
                 the database. The information extracted through this
                 process is the internal design specifications of the
                 sensor. Significant experimental and theoretical
                 results related to GP based data mining for reverse
                 engineering and the related uncertainties will be
  notes =        "CEC 2007 - A joint meeting of the IEEE, the EPS, and
                 the IET.

                 IEEE Catalog Number: 07TH8963C",

Genetic Programming entries for James F Smith III