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Forecasting Models for Hydropower Unit Stability Using LS-SVM
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-28
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper discusses a least square support vector machine (LS-SVM) approach for forecasting stability parameters of Francis turbine unit.
To achieve training and testing data for the models, four field tests were presented, especially for the vibration in Y -direction of lower generator bearing (LGB) and pressure in draft tube (DT).
A heuristic method such as a neural network using Backpropagation (NNBP) is introduced as a comparison model to examine the feasibility of forecasting performance.
In the experimental results, LS-SVM showed superior forecasting accuracies and performances to the NNBP, which is of significant importance to better monitor the unit safety and potential faults diagnosis.
American Psychological Association (APA)
Qiao, Liangliang& Chen, Qijuan. 2015. Forecasting Models for Hydropower Unit Stability Using LS-SVM. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073570
Modern Language Association (MLA)
Qiao, Liangliang& Chen, Qijuan. Forecasting Models for Hydropower Unit Stability Using LS-SVM. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1073570
American Medical Association (AMA)
Qiao, Liangliang& Chen, Qijuan. Forecasting Models for Hydropower Unit Stability Using LS-SVM. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1073570
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073570