A Multi-Level And Multi-Scale Evolutionary Modeling System For Scientific Data

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

  author =       "Zhou Kang and Yan Li and Hugo {de Garis} and 
                 Li-Shan Kang",
  title =        "A Multi-Level And Multi-Scale Evolutionary Modeling
                 System For Scientific Data",
  booktitle =    "Proceedings of the 2002 International Joint Conference
                 on Neural Networks IJCNN'02",
  pages =        "737--742",
  year =         "2002",
  month =        "12-17 " # may,
  address =      "Hilton Hawaiian Village Hotel, Honolulu, Hawaii",
  publisher =    "IEEE Press",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  organisation = "IEEE",
  ISBN =         "0-7803-7278-6",
  keywords =     "genetic algorithms, genetic programming, KDD, complex
                 system, data mining, flood season, macroscopic level
                 laws, microscopic level laws, multilevel multiscale
                 evolutionary modelling system, natural fractals,
                 observed time series modelling, observed time series
                 prediction, ordinary differential equations, scientific
                 data, scientific law discovery, submicroscopic level
                 laws, sunspot series, data mining, differential
                 equations, evolutionary computation, fractals, natural
                 sciences computing, neural nets",
  DOI =          "doi:10.1109/IJCNN.2002.1005565",
  abstract =     "The discovery of scientific laws is always built on
                 the basis of scientific experiments and observed data.
                 Any real world complex system must be controlled by
                 some basic laws, including macroscopic level,
                 submicroscopic level and microscopic level laws. How to
                 discover its necessity-laws from these observed data is
                 the most important task of data mining (DM) and KDD.
                 Based on the evolutionary computation, this paper
                 proposes a multi-level and multi -scale evolutionary
                 modeling system which models the macro-behaviour of the
                 system by ordinary differential equations while models
                 the micro- behavior of the system by natural fractals.
                 This system can be used to model and predict the
                 scientific observed time series, such as observed data
                 of sunspot and precipitation of flood season, and
                 always get good results.",
  notes =        "IJCNN 2002 Held in connection with the World Congress
                 on Computational Intelligence (WCCI 2002)",

Genetic Programming entries for Zhou Kang Yan Li Hugo de Garis Li-Shan Kang