Predicting the Cost of Rework in High-Rise Buildings Using Graph Convolutional Networks-Reference-Cited by-同舟云学术

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Predicting the Cost of Rework in High-Rise Buildings Using Graph Convolutional Networks

Published:2024-08 Issue:8 Volume:150 Page:
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Mostofi Fatemeh¹^ORCID,Tokdemir Onur Behzat²^ORCID,Toğan Vedat³^ORCID,Arditi David⁴^ORCID

Affiliation:

1. Ph.D. Student, Dept. of Civil Engineering, Karadeniz Technical Univ., Trabzon 61080, Turkey (corresponding author). ORCID: .

2. Associate Professor, Dept. of Civil Engineering, Istanbul Technical Univ., Istanbul 34469, Turkey. ORCID: .

3. Professor, Dept. of Civil Engineering, Karadeniz Technical Univ., Trabzon 61080, Turkey. ORCID: .

4. Professor, Dept. of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL 60616. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCEMD4.COENG-14739

Reference99 articles.

1. Assessing Risk Factors Affecting the Accuracy of Conceptual Cost Estimation in the Middle East

2. Cost of quality in Dubai: An analytical case study of residential construction projects

3. FACTORS CAUSING REWORK AND THEIR IMPACT ON PROJECTS’ PERFORMANCE IN EGYPT

4. Machine Learning-Based Model for Predicting the Shear Strength of Slender Reinforced Concrete Beams without Stirrups

5. Classification of rework root causes in the design stage of projects for contract assessment

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