ISSN: 2349-5162

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Published in:

Volume 4 Issue 7
July-2017
eISSN: 2349-5162

Unique Identifier

JETIR1707035

Page Number

177-183

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Title

Performance Evaluation of Neural Networks in Daily Streamflow Forecasting

ISSN

2349-5162

Cite This Article

"Performance Evaluation of Neural Networks in Daily Streamflow Forecasting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 7, page no.177-183, JULY - 2017, Available :http://www.jetir.org/papers/JETIR1707035.pdf

Abstract

Stream flows are often treated as estimates of runoff from watershed of a stream. Stream flow information is required to reduce uncertainty and permit decisions on water resource planning and design. Neural Network model is formulated to predict daily river flows in river Godavari at Perur using Gradient Descent back propagation algorithm. To study the performance of the model developed, various statistical performance indices namely correlation coefficient, normalised root mean square error, coefficient of efficiency, average absolute relative error and threshold statistic are computed during training and testing phases. The results indicate that ANN can effectively be used to model daily streamflows.

Key Words

Streamflow, Artificial Neural Networks, Gradient Descent algorithm

Cite This Article

"Performance Evaluation of Neural Networks in Daily Streamflow Forecasting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 7, page no. pp177-183, JULY - 2017, Available at : http://www.jetir.org/papers/JETIR1707035.pdf

Publication Details

Published Paper ID: JETIR1707035
Registration ID: 180546
Published In: Volume 4 | Issue 7 | Year July-2017
DOI (Digital Object Identifier): http://doi.one/10.1729/IJCRT.17756
Page No: 177-183
ISSN Number: 2349-5162

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Cite This Article

"Performance Evaluation of Neural Networks in Daily Streamflow Forecasting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 7, page no. pp177-183, JULY - 2017, Available at : http://www.jetir.org/papers/JETIR1707035.pdf




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