Journal of applied mathematics & informatics

  • 제6권2호
  • /
  • Pages.599-609
  • /
  • 1999
  • /
  • 2734-1194(pISSN)
  • /
  • 2234-8417(eISSN)
한국전산응용수학회 (The Korean Society for Computational and Applied Mathematics)
권호 표지

COMPARISON OF VARIABLE SELECTION AND STRUCTURAL SPECIFICATION BETWEEN REGRESSION AND NEURAL NETWORK MODELS FOR HOUSEHOLD VEHICULAR TRIP FORECASTING

  • Yi, Jun-Sub (Department of Management Infrmation Systems Kyungsung University)
  • 발행 : 1999.06.01

⟨ 이전 논문 다음 논문 ⟩

초록

Neural networks are explored as an alternative to a regres-sion model for prediction of the number of daily household vehicular trips. This study focuses on contrasting a neural network model with a regression model in term of variable selection as well as the appli-cation of these models for prediction of extreme observations, The differences in the models regarding data transformation variable selec-tion and multicollinearity are considered. The results indicate that the neural network model is a viable alternative to the regression model for addressing both messy data problems and limitation in variable structure specification.

키워드

참고문헌

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