@article{(Open Science Index):https://publications.waset.org/pdf/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.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {8},
	  year      = {2009},
	  pages     = {2134 - 2139},
	  ee        = {https://publications.waset.org/pdf/10991},
	  url   	= {https://publications.waset.org/vol/32},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 32, 2009},
	}