@article{(Open Science Index):https://publications.waset.org/pdf/7572,
	  title     = {Application of Neural Network for Contingency Ranking Based on Combination of Severity Indices},
	  author    = {S. Jadid and  S. Jalilzadeh},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, an improved technique for contingency
ranking using artificial neural network (ANN) is presented. The
proposed approach is based on multi-layer perceptrons trained by
backpropagation to contingency analysis. Severity indices in dynamic
stability assessment are presented. These indices are based on the
concept of coherency and three dot products of the system variables.
It is well known that some indices work better than others for a
particular power system. This paper along with test results using
several different systems, demonstrates that combination of indices
with ANN provides better ranking than a single index. The presented
results are obtained through the use of power system simulation
(PSS/E) and MATLAB 6.5 software.},
	    journal   = {International Journal of Computer and Systems Engineering},
	  volume    = {1},
	  number    = {11},
	  year      = {2007},
	  pages     = {3590 - 3593},
	  ee        = {https://publications.waset.org/pdf/7572},
	  url   	= {https://publications.waset.org/vol/11},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 11, 2007},
	}