NDLI: Comparison of generalized regression neural network and MLP performances on hydrologic data forecasting

Content Provider	IEEE Xplore Digital Library
Author	Yidirim, T. Cigizoglu, H.K.
Copyright Year	2002
Description	Author affiliation: Dept. of Electron. & Commun., Yildiz Univ., Istanbul, Turkey (Yidirim, T.)
Abstract	The estimation and forecasting of the hydrologic data carry significance for many water resources engineering problems. Establishing sediment monitoring instruments on rivers is a costly operation. The methods available in literature for sediment concentration estimation are complicated, time consuming and necessitate cumbersome parameter estimation procedures. Artificial neural networks have been applied to many kinds of hydrologic data within the last two decades. In the majority of these studies standard feed forward multilayer perceptron is employed, In this study the generalized regression neural networks are applied to the selected daily flow and sediment concentration data together with the multilayer perceptron. In both the forecasting the sediment values using the previous observed sediment values and the sediment concentration estimation using the observed river flow values the generalized regression neural networks found superior to the feed forward multilayer perceptron.
Sponsorship	Asia-Pacific Neural Network Assembly Singapore Neuroscience Assoc. SEAL & FSKD Conference Steering Committees IEEE Neural Networks Soc. Int. Neural Network Soc. Eur. Neural Network Soc. SPIE
Starting Page	2488
Ending Page	2491
File Size	329166
Page Count	4
File Format	PDF
ISBN	9810475241
DOI	10.1109/ICONIP.2002.1201942
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-18
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Nanyang Technological University
Subject Keyword	Neural networks Sediments Multilayer perceptrons Rivers Artificial neural networks Feeds Multi-layer neural network Feedforward neural networks Water resources Data engineering
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A Neural Smith Chart Application

A New Short Term Load Forecasting Using Multilayer Perceptron

Technique of learning rate estimation for efficient training of MLP

Mongolian character recognition using multilayer perceptron (MLP)

Water Demand Forecasting Using Multi-layer Perceptron and Radial Basis Functions

A unifying viewpoint of multilayer perceptrons and hidden Markov models

GSM RSSI-based positioning using extended Kalman filter for training artificial neural networks

Morphological perceptrons

Logistic Model Tree Extraction From Artificial Neural Networks

Comparison of generalized regression neural network and MLP performances on hydrologic data forecasting

Similar Documents

A Neural Smith Chart Application

A New Short Term Load Forecasting Using Multilayer Perceptron

Technique of learning rate estimation for efficient training of MLP

Mongolian character recognition using multilayer perceptron (MLP)

Water Demand Forecasting Using Multi-layer Perceptron and Radial Basis Functions

A unifying viewpoint of multilayer perceptrons and hidden Markov models

GSM RSSI-based positioning using extended Kalman filter for training artificial neural networks

Morphological perceptrons

Logistic Model Tree Extraction From Artificial Neural Networks

Comparison of generalized regression neural network and MLP performances on hydrologic data forecasting