Comparison of data-driven modelling techniques for river flow forecasting-Reference-Cited by-同舟云学术

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Comparison of data-driven modelling techniques for river flow forecasting

Published:2010-10-12 Issue:7 Volume:55 Page:1163-1174
ISSN:0262-6667
Container-title:Hydrological Sciences Journal
language:en
Short-container-title:Hydrological Sciences Journal

Author:

Londhe Shreenivas¹,Charhate Shrikant²

Affiliation:

1. a Department of Civil Engineering , Vishwakarma Institute of Information Technology, Survey no. 2/3/4, Kondhwa (Bk) , Pune, MH, 411048, India

2. b Department of Civil Engineering , Datta Meghe College of Engineering, Airoli , Navi Mumbai, MH, 400708, India

Publisher

Informa UK Limited

Subject

Water Science and Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/02626667.2010.512867

Reference37 articles.

1. Added gains of soil moisture content observations for streamflow predictions using neural networks

2. Artificial Neural Networks in Hydrology. I: Preliminary Concepts

3. Neural networks and M5 model trees in modelling water level–discharge relationship

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