Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10991,
  title    = {Principal Component Analysis-Ranking as a Variable Selection Method for the Simultaneous Spectrophotometric Determination of Phenol, Resorcinol and Catechol in Real Samples},
  author    = {Nahid Ghasemi and  Mohammad Goodarzi and  Morteza Khosravi},
  country   = {},
  institution={},
  abstract  = {Simultaneous determination of multicomponents of phenol, resorcinol and catechol with a chemometric technique a PCranking artificial neural network (PCranking-ANN) algorithm is reported in this study. Based on the data correlation coefficient method, 3 representative PCs are selected from the scores of original UV spectral data (35 PCs) as the original input patterns for ANN to build a neural network model. The results obtained by iterating 8000 .The RMSEP for phenol, resorcinol and catechol with PCranking- ANN were 0.6680, 0.0766 and 0.1033, respectively. Calibration matrices were 0.50-21.0, 0.50-15.1 and 0.50-20.0 μg ml-1 for phenol, resorcinol and catechol, respectively. The proposed method was successfully applied for the determination of phenol, resorcinol and catechol in synthetic and water samples.
},
  {International Journal of Computer and Information Engineering },  volume    = {3},
  number    = {8},
  year      = {2009},
  pages     = {2134 - 2139},
  ee        = {http://waset.org/publications/10991},
  url       = {http://waset.org/Publications?p=32},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 32, 2009},
}