A novel approximation method for multivariate data partitioning Fluctuation free integration based HDMR


Tunga B., DEMIRALP M.

ENGINEERING COMPUTATIONS, vol.29, pp.743-765, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 29
  • Publication Date: 2012
  • Doi Number: 10.1108/02644401211257245
  • Journal Name: ENGINEERING COMPUTATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.743-765
  • Istanbul Technical University Affiliated: No

Abstract

Purpose - The plain High Dimensional Model Representation (HDMR) method needs Dirac delta type weights to partition the given multivariate data set for modelling an interpolation problem. Dirac delta type weight imposes a different importance level to each node of this set during the partitioning procedure which directly effects the performance of HDMR. The purpose of this paper is to develop a new method by using fluctuation free integration and HDMR methods to obtain optimized weight factors needed for identifying these importance levels for the multivariate data partitioning and modelling procedure.