WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/9997044,
	  title     = {The Use Support Vector Machine and Back  Propagation Neural Network for Prediction of Daily  Tidal Levels along the Jeddah Coast, Saudi Arabia},
	  author    = {E. A. Mlybari and  M. S. Elbisy and  A. H. Alshahri and  O. M. Albarakati},
	  country	= {},
	  institution	= {},
	  abstract     = {Sea level rise threatens to increase the impact of future 
storms and hurricanes on coastal communities. Accurate sea level 
change prediction and supplement is an important task in determining 
constructions and human activities in coastal and oceanic areas. In 
this study, support vector machines (SVM) is proposed to predict 
daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal 
parameter values of kernel function are determined using a genetic 
algorithm. The SVM results are compared with the field data and 
with back propagation (BP). Among the models, the SVM is superior 
to BPNN and has better generalization performance.

 
},
	    journal   = {International Journal of Civil and Environmental Engineering},
	  volume    = {8},
	  number    = {1},
	  year      = {2014},
	  pages     = {13 - 18},
	  ee        = {https://publications.waset.org/pdf/9997044},
	  url   	= {https://publications.waset.org/vol/85},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 85, 2014},
	}