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

Tunga B., DEMIRALP M.

ENGINEERING COMPUTATIONS, cilt.29, ss.743-765, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1108/02644401211257245
  • Dergi Adı: ENGINEERING COMPUTATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.743-765
  • İstanbul Teknik Üniversitesi Adresli: Hayır

Özet

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.