Data Mining and Knowledge Discovery in Sediment Transport

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Vladan Babovic",
  title =        "Data Mining and Knowledge Discovery in Sediment
  journal =      "Computer-Aided Civil and Infrastructure Engineering",
  year =         "2000",
  volume =       "15",
  number =       "5",
  pages =        "383--389",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1093-9687",
  DOI =          "doi:10.1111/0885-9507.00202",
  size =         "7 pages",
  abstract =     "The means for data collection have never been as
                 advanced as they are today. Moreover, the numerical
                 models we use today have never been so advanced.
                 Feeding and calibrating models against collected
                 measurements, however, represents only a one-way flow:
                 from measurements to the model. The observations of the
                 system can be analyzed further in the search for the
                 information they encode. Such automated search for
                 models accurately describing data constitutes a new
                 direction that can be identified as that of data
                 mining. It can be expected that in the years to come we
                 shall concentrate our efforts more and more on the
                 analysis of the data we acquire from natural or
                 artificial sources and that we shall mine for knowledge
                 from the data so acquired.

                 Data mining and knowledge discovery aim at providing
                 tools to facilitate the conversion of data into a
                 number of forms, such as equations, that provide a
                 better understanding of the process generating or
                 producing these data. These new models combined with
                 the already available understanding of the physical
                 processes -- the theory -- result in an improved
                 understanding and novel formulations of physical laws
                 and improved predictive capability.

                 This article describes the data mining process in
                 general, as well as an application of a data mining
                 technique in the domain of sediment transport. Data
                 related to the concentration of suspended sediment near
                 a bed are analyzed by the means of genetic programming.
                 Machine-induced relationships are compared against
                 formulations proposed by human experts and are
                 discussed in terms of accuracy and physical
  notes =        "Article first published online: 17 DEC 2002",

Genetic Programming entries for Vladan Babovic