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

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REZAZADEH JOUDI ALI; SATTARI MOHAMMAD TAGHI

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Journal: Journal of Range and Watershed Managment Year:2017 | Volume:70 | Issue:2 Page(s): 345-358

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Title

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 | Issue Writer Certificate

Keywords

K-NEAREST NEIGHBORSQ1

LIGHVANCHAYRIVERQ1

DATA MININGQ1

SUPPORT VECTOR REGRESSIONQ1

SUSPENDED SEDIMENT LOADQ1

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.

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APA: Copy

REZAZADEH JOUDI, ALI, & SATTARI, MOHAMMAD TAGHI. (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. SID. https://sid.ir/paper/162662/en

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)[Internet]. 2017;70(2):345-358. Available from: https://sid.ir/paper/162662/en

IEEE: Copy

ALI REZAZADEH JOUDI, and MOHAMMAD TAGHI SATTARI, “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), vol. 70, no. 2, pp. 345–358, 2017, [Online]. Available: https://sid.ir/paper/162662/en

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