Guiding Genetic Program Based Data Mining Using Fuzzy Rules

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{smith:2006:IDEAL,
  author =       "James F. {Smith, III} and ThanhVu H. Nguyen",
  title =        "Guiding Genetic Program Based Data Mining Using Fuzzy
                 Rules",
  booktitle =    "Intelligent Data Engineering and Automated Learning
                 IDEAL 2006",
  year =         "2006",
  editor =       "Emilio Corchado and HujunYin and Vicente Botti and 
                 Colin Fyfe",
  volume =       "4224",
  series =       "Lecture Notes in Computer Science",
  pages =        "1337--1345",
  address =      "Burgos, Spain",
  month =        sep # " 20-23",
  publisher =    "Springer",
  note =         "Special Session on Nature-Inspired Date Technologies",
  keywords =     "genetic algorithms, genetic programming, Fuzzy Logic,
                 Data Mining, Control Algorithms, Planning Algorithms,
                 UAV",
  isbn13 =       "978-3-540-45485-4",
  DOI =          "doi:10.1007/11875581_159",
  size =         "9 pages",
  abstract =     "A data mining procedure for automatic determination of
                 fuzzy decision tree structure using a genetic program
                 is discussed. A genetic program (GP) is an algorithm
                 that evolves other algorithms or mathematical
                 expressions. Methods for accelerating convergence of
                 the data mining procedure are examined. The methods
                 include introducing fuzzy rules into the GP and a new
                 innovation based on computer algebra. Experimental
                 results related to using computer algebra are given.
                 Comparisons between trees created using a genetic
                 program and those constructed solely by interviewing
                 experts are made. Connections to past GP based data
                 mining procedures for evolving fuzzy decision trees are
                 established. Finally, experimental methods that have
                 been used to validate the data mining algorithm are
                 discussed.",
  notes =        "A genetic program (GP) has been used as a data mining
                 (DM) function to automatically create decision logic
                 for two different resource managers (RMs). The most
                 recent of the RMs, referred to as the UAVRM is the
                 topic of this paper. It automatically controls a group
                 of unmanned aerial vehicles (UAVs) that are
                 cooperatively making atmospheric measurements.

                 The DM procedure that uses a GP as a data mining
                 function to create a subtree of UAVRM is discussed. The
                 resulting decision logic for the RMs is rendered in the
                 form of fuzzy decision trees. The fitness function,
                 bloat control methods, data base, etc., for the tree to
                 be evolved are described. Innovative bloat control
                 methods using computer algebra based simplification are
                 given. A subset of the fuzzy rules used by the GP to
                 help accelerate convergence of the GP and improve the
                 quality of the results is provided. Experimental
                 methods of validating the evolved decision logic are
                 discussed to support the effectiveness of the data
                 mined results.",
}

Genetic Programming entries for James F Smith III ThanhVu Nguyen

Citations