Stream Flow Behaviour Studies using Neural Networks
Journal Title: International Journal of Engineering and Science Invention - Year 2017, Vol 6, Issue 10
Abstract
Flow characteristics of streams are complicated and are influenced by different hydraulic parameters. Although numerical analysis has its own importance, soft computing techniques are becoming popular with availability of high speed computers. Soft computing proves to predict in a better way with sufficient and reliable data sets. Discharge requirement of stream flow is always needed for planning, design and execution of any water resources system. Discharge data of a river at two gauging stations namely Panposh and Gomlai were used for analysis. Four neural networks were used for analysis of data on a common platform and it is assessed that Cascade followed by RBF gave better predictions. Model equations were framed for the stream flow using the network interpretation diagram.
Authors and Affiliations
Alok Adhikari, Nibedita Adhikari, Kanhu Charan Patra
Keywords
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