Beta
116136

ARTIFICIAL NEURAL NETWORK MODEL FOR PREDICTING DISCHARGE BELOW GATES

Article

Last updated: 23 Jan 2023

Subjects

-

Tags

Civil Engineering: structural, Geotechnical, reinforced concrete and s…nd sanitary engineering, Hydraulic, Railway, construction Management.

Abstract

Gate in general, a device in which a leaf or a member is moved across the water from external position to control or stop the flow. Under flow gates commonly used to regulate and measure flow in hydraulic structures. In this paper, Multiplayer feed forward Artificial Network (ANN) with back propagation algorithm is used to develop a computational model to predict discharge below gates. A network of size 3-9-1 is found suitable for this purpose with 540 iterations and hyperbolic tangent (tanch) activation function. The results of the trained, verified and tested ANN model are compared to the experimental measurements. The results indicated that the ANNs are powerful tools for modeling flow rates below gates.

DOI

10.21608/jesaun.2008.116136

Authors

First Name

Amen,

Last Name

K.A.

MiddleName

-

Affiliation

Civil Engineering Department, Faculty of Engineering, Assiut University

Email

-

City

-

Orcid

-

Volume

36

Article Issue

No 3

Related Issue

16832

Issue Date

2008-05-01

Receive Date

2008-01-19

Publish Date

2008-05-01

Page Start

581

Page End

587

Print ISSN

1687-0530

Online ISSN

2356-8550

Link

https://jesaun.journals.ekb.eg/article_116136.html

Detail API

https://jesaun.journals.ekb.eg/service?article_code=116136

Order

2

Type

Research Paper

Type Code

1,438

Publication Type

Journal

Publication Title

JES. Journal of Engineering Sciences

Publication Link

https://jesaun.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

23 Jan 2023