The use of genetic programming for the construction of a financial management model in an enterprise

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  author =       "Wen-Tsao Pan",
  title =        "The use of genetic programming for the construction of
                 a financial management model in an enterprise",
  journal =      "Applied Intelligence",
  year =         "2012",
  number =       "2",
  volume =       "36",
  pages =        "271--279",
  keywords =     "genetic algorithms, genetic programming, grey
                 relational analysis, cluster analysis, back-propagation
                 neural network, data mining",
  DOI =          "doi:10.1007/s10489-010-0259-7",
  size =         "9 pages",
  abstract =     "The fast development in China's economy has caused the
                 rapid expansion of the domestic market. Since many
                 economists do not have optimistic views regarding the
                 bubble economy of China, it is necessary for Taiwanese
                 businessmen to understand in-depth the business
                 operational performance and financial situation of
                 enterprises in China, so as to reduce the risk of a
                 potential investment. In this article, data from the
                 China Economic Research Database (CCER), the financial
                 database of financial corporations are collected for
                 analysis to investigate the business operation and
                 management performance and financial characteristic of
                 enterprises in China. In this article, grey relational
                 analysis is applied first in order to investigate the
                 business operational performance of 600 enterprises in
                 China. Afterwards, a more recent clustering technique
                 is used to divide, based on financial characteristic,
                 enterprises in China into two groups. Finally, three
                 models, namely genetic programming, Back-Propagation
                 Neural Network and Logistic Regression are adopted to
                 construct an Enterprise Operational Performance model
                 and an Enterprise Finance Characteristic model,
                 respectively. Based on the results found, it can be
                 concluded that genetic programming yielded the best
                 classification and forecast performance, compared to
                 the other three techniques.",
  affiliation =  "Department of Information Management, Fooyin
                 University, 3F., No. 12, Lane 271, Longjiang Rd.,
                 Jhongshan District, Taipei City, 104 Taiwan, ROC",
  bibdate =      "2012-02-24",
  bibsource =    "DBLP,

Genetic Programming entries for Wen-Tsao Pan