The use of computational intelligence base models in suspended sediment load estimation (Case study: Gillan province)

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ASADI MARYAM; FATHZADEH ALI

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Journal: Journal of Range and Watershed Managment Year:2018 | Volume:71 | Issue:1 Page(s): 45-60

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Title

The use of computational intelligence base models in suspended sediment load estimation (Case study: Gillan province)

Author(s)

ASADI MARYAM | FATHZADEH ALI | Issue Writer Certificate

Keywords

Suspended sediment loadQ1

Sediment Rating CurveQ1

Gaussian processQ1

data miningQ1

Artificial intelligentQ1

Abstract

Understanding of suspended sediment rate is one of the fundamental problems in water projects which water engineers consistently have involved with it. Wrong estimations in sediment transport cause incorrect design and destruction of hydraulic systems. Due to the difficulty of suspended sediment measurements, Sediment Rating Curves is considered as the most common method for estimating the Suspended sediment load. The main purpose of this research is the capability challenge of this method in comparison to some state of the art models. In this study, we selected some computational intelligence models (i. e. K-nearest neighbor (KNN), artificial neural networks (ANN), Gaussian processes (GP), decision trees of M5, support vector machine (SVM) and evolutionary support vector machine (ESVM)) and compared them with their sediment rating model in 8 basins located in Gilan province. Daily sediment and discharge data considered as the input data for 30-years. Evaluation of the results indicated that the Gaussian process model has the lowest residual sum of squares (RMSE) and the highest correlation coefficient (r) than the other models.

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APA: Copy

ASADI, MARYAM, & FATHZADEH, ALI. (2018). The use of computational intelligence base models in suspended sediment load estimation (Case study: Gillan province). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 71(1 ), 45-60. SID. https://sid.ir/paper/162600/en

Vancouver: Copy

ASADI MARYAM, FATHZADEH ALI. The use of computational intelligence base models in suspended sediment load estimation (Case study: Gillan province). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2018;71(1 ):45-60. Available from: https://sid.ir/paper/162600/en

IEEE: Copy

MARYAM ASADI, and ALI FATHZADEH, “The use of computational intelligence base models in suspended sediment load estimation (Case study: Gillan province),” JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 71, no. 1 , pp. 45–60, 2018, [Online]. Available: https://sid.ir/paper/162600/en

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