@article{(Open Science Index):https://publications.waset.org/pdf/10001932,
	  title     = {Application and Assessment of Artificial Neural Networks for Biodiesel Iodine Value Prediction},
	  author    = {Raquel M. de Sousa and  Sofiane Labidi and  Allan Kardec D. Barros and  Alex O. Barradas Filho and  Aldalea L. B. Marques},
	  country	= {},
	  institution	= {},
	  abstract     = {Several parameters are established in order to measure
biodiesel quality. One of them is the iodine value, which is an
important parameter that measures the total unsaturation within a
mixture of fatty acids. Limitation of unsaturated fatty acids is
necessary since warming of higher quantity of these ones ends in
either formation of deposits inside the motor or damage of lubricant.
Determination of iodine value by official procedure tends to be very
laborious, with high costs and toxicity of the reagents, this study uses
artificial neural network (ANN) in order to predict the iodine value
property as an alternative to these problems. The methodology of
development of networks used 13 esters of fatty acids in the input
with convergence algorithms of back propagation of back
propagation type were optimized in order to get an architecture of
prediction of iodine value. This study allowed us to demonstrate the
neural networks’ ability to learn the correlation between biodiesel
quality properties, in this caseiodine value, and the molecular
structures that make it up. The model developed in the study reached
a correlation coefficient (R) of 0.99 for both network validation and
network simulation, with Levenberg-Maquardt algorithm.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {5},
	  year      = {2015},
	  pages     = {1369 - 1373},
	  ee        = {https://publications.waset.org/pdf/10001932},
	  url   	= {https://publications.waset.org/vol/101},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 101, 2015},