Diagnosing and Identifying Factors affecting the Prediction of Duration for Construction Projects Using Artificial Neural Network: Systematic Review

Authors

  • abbas hameed Al-Nahrain University
  • Faiq M.S. Al-Zwainy Al-Nahrain University

Keywords:

Construction Projects, Predict, Durations, Artificial Neural Networks, Critical Factors, Systematic Review

Abstract

The current study dealt with one of the most important problems that the construction projects suffer from, which is the deviation of the planned duration  in the construction projects, as the deviation of the duration has become a critical issue facing this type of projects. The critical impact that affects the prediction of the duration of construction projects using artificial neural network in the past 25 years. In this context, the main objective of the study was to conduct a systematic review of the literature in the field of determining the most important critical factors affecting the estimation of the time periods of construction projects using the artificial neural network, according to the recognized scientific contexts in the field of systematic review, through a literature review. This dealt with this subject for the period extending from 1996 to 2021. For the purpose of achieving the objectives of the study, a systematic review was conducted based on the database (Google Scholar), (EBSCO) and (Research gate), and the study concluded that there are 236 influential factors in predicting the duration of construction projects. It was divided according to the main axes: residential projects and the most important factors influencing them (the efficiency of the project manager, support for senior management, the number of floors and the building area), infrastructure projects represented by roads, irrigation and drainage, and the most important factors are the following (the initial cost and length of the project, the number of intersections, and earthworks, Furniture, weather conditions, project size, and institutional and business projects represented by school buildings, and the most important factors are as follows (change orders and experience The supervising engineer, the duration of the contract, and the rank of the contracting company), in addition to the industrial projects represented by industrial buildings, the most important of which are (type of work, type of contract, capital and work location).

Downloads

Published

2022-09-19

How to Cite

1.
حميد ع, فائق محمد سرحان الزويني. Diagnosing and Identifying Factors affecting the Prediction of Duration for Construction Projects Using Artificial Neural Network: Systematic Review. Tuj-eng [Internet]. 2022Sep.19 [cited 2024Dec.23];44(4):231-52. Available from: https://journal.tishreen.edu.sy/index.php/engscnc/article/view/12580

Issue

Vol. 44 No. 4 (2022): Tishreen University Journal of Research and Scientific Studies - Engineering Sciences Series

Section

Master student researches

License

Copyright (c) 2022 ttps://creativecommons.org/licenses/by-nc-sa/4.0/

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The authors retain the copyright and grant the right to publish in the magazine for the first time with the transfer of the commercial right to Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series

 Under a CC BY- NC-SA 04 license that allows others to share the work with of the work's authorship and initial publication in this journal. Authors can use a copy of their articles in their scientific activity, and on their scientific websites, provided that the place of publication is indicted in  Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series   .  The Readers have the right to send, print and subscribe to the initial version of the article, and the title of  Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series     Publisher

journal uses a CC BY-NC-SA license which mean

You are free to:

  • Adapt — remix, transform, and build upon the material
  •  
  • The licensor cannot revoke these freedoms as long as you follow the license terms.

 

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • NonCommercial — You may not use the material for commercial purposes.
  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.