NDLI: Design and implementation of a visual modeling tool to support interactive runoff forecasting

Content Provider	IEEE Xplore Digital Library
Author	Mutao Huang Yong Tian
Copyright Year	2010
Description	Author affiliation: College of Hydropower & Information Engineering, Huazhong University of Science & Technology, Wuhan, China (Mutao Huang; Yong Tian)
Abstract	To tackle the problems of low modeling efficiencies involved in implementing runoff forecasting using conventional modeling technologies, a visual modeling tool is established by integrating a visual modeling editor with the artificial neural network (ANN) modular to support interactive and fast modeling of the complex and dynamic runoff process. The workflow of visual modeling includes the prediction schema definition, ANN architecture design, data processing, ANN training and validation, runoff forecasting. In particular, to facilitate the user's activities for runoff simulation, an operational data exchange and model linking mechanism is proposed to allow for interoperability between models and multi-data sources. A case study for interactive runoff forecasting is given for Qingjiang River basin located in the middle part of China. A serial simulation experiments were carried out to verify the feasibility of the visual tool, and the results show that the tool can greatly enhance the easy-to-use capabilities of visual modeling and appeal in offering a positive prospect of improving the efficiency and robustness of current practice in hydrological modeling.
Starting Page	270
Ending Page	274
File Size	1268386
Page Count	5
File Format	PDF
ISBN	9781424465828
e-ISBN	9781424465859
DOI	10.1109/ICICISYS.2010.5658692
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Artificial neural networks Predictive models Artificial neural network Visual modeling Forecasting Runoff forecast Intelligent system Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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