Beta
ManageSearchChatDiscover
243943

Modeling of Pavement Maintenance Decisions Using Artificial Intelligence Based on Maintenance Unit.

Article

Last updated: 22 Jan 2023

OverviewSimilar Items

Subjects

-

Tags

Civil Engineering

Abstract

Recently, all efforts have been directed toward keeping the network functional at a high level by determining the appropriate maintenance or rehabilitation (M & R) treatment. Determining the appropriate M & R strategies for flexible pavements is a complex process and is considered a key component of the Pavement Maintenance Management System (PMMS). Since such a decision system is complex, automated implementation using a pre-trained model via an artificial neural network (ANN) approach is a critical tool for decision-makers. Many studies have been conducted on modeling pavement condition index using ANN to determine the maintenance decision. The Egyptian Code of Practice has recently relied on the maintenance unit (MU) concept for maintenance decision prediction. A few researchers have investigated maintenance decision (MD) predications using the MU modeling by ANN but have not adequately studied Egyptian Code consideration. Therefore, this paper addresses the application of the latest machine learning technique for forecasting the current pavement maintenance decisions based on the MU system according to the Egyptian code considerations to develop a one-step enhanced decision-making tool. A pattern-recognition algorithm (neural network) was applied to 54.3 km of surveyed roads in Minia governorate, Egypt.  The results indicated that the ANN model is capable of predicting the MD with a high level of reliability, with a mean square error (MSE) value of 0.02993, 0.03046, and 0.03018, and a percentage error (% E) value of 13.29693, 14.11734, and 13.83215 for the training, validation, and testing datasets, respectively. 

DOI

10.21608/bfemu.2022.243943

Keywords

Pavement Distress, Pavement maintenance, Maintenance Decision, Maintenance Unit, artificial neural network

Authors

First Name

Hamdy

Last Name

Faheem

MiddleName

B.

Affiliation

Associate Professor of Highway and Traffic Engineering, Dept. of Civil Engineering, Faculty of Engineering, Minia University

Email

hamdyfaheem@mu.edu.eg

City

Minia

Orcid

-

First Name

Afaf

Last Name

Mahmoud

MiddleName

A.

Affiliation

Professor of Highway and Airport Engineering, Dept. of Civil Engineering, Faculty of Engineering, Minia University,

Email

afaf.abdelhaleem@mu.edu.eg

City

minia

Orcid

-

First Name

Mostafa

Last Name

Hashem

MiddleName

D.

Affiliation

Professor of Highway and Airport Engineering, Dept. of Civil Engineering, Faculty of Engineering, Minia University

Email

mostafa.deeb@mu.edu.eg

City

minia

Orcid

-

First Name

Mohamed

Last Name

A. Abd El moez

MiddleName

-

Affiliation

Demonstrator, Dept. of Civil Engineering, Faculty of Engineering, Minia.

Email

-

City

Minia

Orcid

-

Volume

47

Article Issue

3

Related Issue

34982

Issue Date

2022-06-01

Receive Date

2022-02-09

Publish Date

2022-06-14

Page Start

10

Page End

21

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 47_Issue 3_Pages 10-21.pdf

PDF . 2.2MB

Link

https://bfemu.journals.ekb.eg/article_243943.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=243943

Order

1

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023