Learning spectrum's selection in OLAM network for analysis cement samples

Ning Huang, Peng Wang, Dai Quan Tang, Ren Lan Hu

Research output: Contribution to journalArticlepeer-review


It uses OLAM artificial neural network to analyze the samples of cement raw material Two kinds of spectrums are used for network learning: pure-element spectrum and mix-element spectrum. The output of pure-element method can be used to construct a simulate spectrum, which can be compared with the original spectrum and judge the shift of spectrum; the mix-element method can store more message and correct the matrix effect, but the multicollinearity among spectrums can cause some side effect to the results.

Original languageEnglish
Pages (from-to)93-95+70
JournalHedianzixue Yu Tance Jishu/Nuclear Electronics and Detection Technology
Issue number1
StatePublished - Jan 2010
Externally publishedYes


  • Learning Spectrum Selection
  • OLAM
  • Raw material of Cement
  • XRF


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