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A data-driven algorithm for constructing artificial neural network rainfall-runoff models

✍ Scribed by K. P. Sudheer; A. K. Gosain; K. S. Ramasastri

Publisher
John Wiley and Sons
Year
2002
Tongue
English
Weight
104 KB
Volume
16
Category
Article
ISSN
0885-6087

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✦ Synopsis

Abstract

A new approach for designing the network structure in an artificial neural network (ANN)‐based rainfall‐runoff model is presented. The method utilizes the statistical properties such as cross‐, auto‐ and partial‐auto‐correlation of the data series in identifying a unique input vector that best represents the process for the basin, and a standard algorithm for training. The methodology has been validated using the data for a river basin in India. The results of the study are highly promising and indicate that it could significantly reduce the effort and computational time required in developing an ANN model. Copyright © 2002 John Wiley & Sons, Ltd.

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