Estimation of Suspended Sediment Load Using Artificial Neural Network in Khour Al Zubair Port, Iraq

• Autorzy: Hassan Ayman A. , Ibrahim Husham T. , Al-Aboodi Ali H.

Identyfikatory

DOI

10.12911/22998993/162400

• Języki publikacji: EN

Abstrakty

EN

The port of Khour Al-Zubair is located 60.0 km south of the city centre of Basrah; it is also located 105.0 kilometres from the northern tip of the Arabian Gulf. The main goal of this paper is to estimate the concentration of suspended deposit (SSC) in “Khour Al-Zubair” port using a Multilayer Perceptron Neural Network (MLP) based on hydraulic and local boundary parameters while also studying the effect of these parameters on estimating the SSC. Five input parameters (channel width, water depth, discharge, cross-section area, and flow velocity) are used for estimating SSC. Different input hydraulic and local boundary parameter combinations in the three sections (port center, port south, and port north) were used for creating nine models. The use of both hydraulic and local boundary parameters for SSC estimation is very important in the port area for estimating sediment loads without the need for field measurements, which require effort and time.

Słowa kluczowe

EN

suspended sediment concentration; multilayer perceptron; neural network; Khour Al-Zubair port; Basrah city

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2023
• Tom: Vol. 24, nr 6
• Strony: 54--64
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Hassan Ayman A.

• Department of Civil Engineering, College of Engineering, University of Basrah, Basrah, Iraq

• https://orcid.org/0000-0002-6711-0066

autor

Ibrahim Husham T.

• Department of Civil Engineering, College of Engineering, University of Basrah, Basrah, Iraq

• https://orcid.org/0000-0002-1504-217X

autor

Al-Aboodi Ali H.

• Department of Civil Engineering, College of Engineering, University of Basrah, Basrah, Iraq

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