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Paper Information

Journal:   JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)   SUMMER 2017 , Volume 70 , Number 2; Page(s) 345 To 358.
 
Paper: 

COMPARISON OF THE EFFICIENCY OF SUPPORT VECTOR REGRESSION AND K-NEAREST NEIGHBOR METHODS IN SUSPENDED SEDIMENT LOAD ESTIMATION IN RIVER (CASE STUDY: LIGHVANCHAY RIVER)

 
 
Author(s):  REZAZADEH JOUDI ALI*, SATTARI MOHAMMAD TAGHI
 
* YOUNG RESEARCHERS AND ELITE CLUB, MARAGHEH BRANCH, ISLAMIC AZAD UNIVERSITY, MARAGHEH, I. R. IRAN
 
Abstract: 

Estimation of suspended sediment load or specifying the damages incured as a result of inattention to such estimation is one of the most important and fundamental challenges in river engineering and sediment transport studies. Given the importance and role of sediment in the design and maintenance of hydraulic structures such as dams, as well its significance in planning for efficient tilization of downstream river and also conservation of nutrients at the upstream of river, many attempts have been made to estimate suspended sediment load of rivers and numerical methods have been developed in this regard. But due to the high cost of most procedures or lack of adequate precision in most common experimental methods, a new method is needed that can estimate suspended sediment load with the greatest possible precision. In this study, the amount of suspended sediment load of Lighvan River has been estimated through support vector regression and k-Nearest neighbor methods. Results indicated the appropriateness of both data mining techniques applied in this study. Among examined methods in this study, the support vector regression method predicted the amount of suspended sediment load in LighvanChay River with representing evaluation indexes such as (CC=0.959, RMSE=43.547 (ton/day)) more accurately than K-nearest neighbor method.

 
Keyword(s): K-NEAREST NEIGHBORS, LIGHVANCHAYRIVER, DATA MINING, SUPPORT VECTOR REGRESSION, SUSPENDED SEDIMENT LOAD
 
 
References: 
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Cite:
APA: Copy

REZAZADEH JOUDI, A., & SATTARI, M. (2017). COMPARISON OF THE EFFICIENCY OF SUPPORT VECTOR REGRESSION AND K-NEAREST NEIGHBOR METHODS IN SUSPENDED SEDIMENT LOAD ESTIMATION IN RIVER (CASE STUDY: LIGHVANCHAY RIVER). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 70(2), 345-358. https://www.sid.ir/en/journal/ViewPaper.aspx?id=545010



Vancouver: Copy

REZAZADEH JOUDI ALI, SATTARI MOHAMMAD TAGHI. COMPARISON OF THE EFFICIENCY OF SUPPORT VECTOR REGRESSION AND K-NEAREST NEIGHBOR METHODS IN SUSPENDED SEDIMENT LOAD ESTIMATION IN RIVER (CASE STUDY: LIGHVANCHAY RIVER). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES). 2017 [cited 2021April12];70(2):345-358. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=545010



IEEE: Copy

REZAZADEH JOUDI, A., SATTARI, M., 2017. COMPARISON OF THE EFFICIENCY OF SUPPORT VECTOR REGRESSION AND K-NEAREST NEIGHBOR METHODS IN SUSPENDED SEDIMENT LOAD ESTIMATION IN RIVER (CASE STUDY: LIGHVANCHAY RIVER). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), [online] 70(2), pp.345-358. Available at: <https://www.sid.ir/en/journal/ViewPaper.aspx?id=545010>.



 
 
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