@article{(Open Science Index):https://publications.waset.org/pdf/267,
	  title     = {Artificial Neural Networks Modeling in Water Resources Engineering: Infrastructure and Applications},
	  author    = {M. R. Mustafa and  M. H. Isa and  R. B. Rezaur},
	  country	= {},
	  institution	= {},
	  abstract     = {The use of artificial neural network (ANN) modeling
for prediction and forecasting variables in water resources
engineering are being increasing rapidly. Infrastructural applications
of ANN in terms of selection of inputs, architecture of networks,
training algorithms, and selection of training parameters in different
types of neural networks used in water resources engineering have
been reported. ANN modeling conducted for water resources
engineering variables (river sediment and discharge) published in
high impact journals since 2002 to 2011 have been examined and
presented in this review. ANN is a vigorous technique to develop
immense relationship between the input and output variables, and
able to extract complex behavior between the water resources
variables such as river sediment and discharge. It can produce robust
prediction results for many of the water resources engineering
problems by appropriate learning from a set of examples. It is
important to have a good understanding of the input and output
variables from a statistical analysis of the data before network
modeling, which can facilitate to design an efficient network. An
appropriate training based ANN model is able to adopt the physical
understanding between the variables and may generate more effective
results than conventional prediction techniques.},
	    journal   = {International Journal of Civil and Environmental Engineering},
	  volume    = {6},
	  number    = {2},
	  year      = {2012},
	  pages     = {128 - 136},
	  ee        = {https://publications.waset.org/pdf/267},
	  url   	= {https://publications.waset.org/vol/62},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 62, 2012},
	}