Data Transformation in Modern Petrol Engine Tune-up

  • Authors:

  • Chi-man Vong;Pak-kin Wong;Yi-ping Li

  • Affiliations:

  • Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macao, cmvong@umac.m, ypli@umac.m;Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Macao, fstpkw@umac.mo;Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macao, cmvong@umac.m, ypli@umac.m

  • Venue:
  • Proceedings of the 2005 conference on Advances in Logic Based Intelligent Systems: Selected Papers of LAPTEC 2005
  • Year:
  • 2005

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Abstract

Data transformation is a kind of data preprocessing [1, 3, 5] and an important procedure for mathematical modelling. Mathematical model estimated based on a training data set results better if the data set has been properly preprocessed before passed to the modelling procedure. In the paper, different preprocessing methods on automotive engine data are examined. The preprocessed data sets using different preprocessing methods are passed to neural networks for models estimation. The generalizations of these estimated models could be verified by applying test sets, which determine the effects of different preprocessing methods. The results of preprocessing methods for automotive engine data are shown in the paper.