Forecasting the Final Cost of Infrastructure Projects in Syria Using Earned Value Management and Artificial Intelligence

Authors

  • Bassam Hassan
  • Samah Makkieh
  • Nver Titizian

Abstract

Syrian construction projects performance generally suffer from failure in term of cost factor. Monitoring and controlling processes under Earned value management methodology (EVM) are insufficient, especially within reconstruction phase; cause, the complex work environment makes the prediction process based on EVM inaccurate. So this search aimed to improve EVM performance in forecasting final cost of Infrastructure projects using artificial neural networks.

Lattakia Ariha highway project was chosen as a case study. The three basic value of EVM were used to obtain parameters which were chosen as inputs to the final cost forecasting network. Then the network was trained on several structures. The structure that corresponding to the smallest error was chosen as the best predictive structure.

The training phase showed that the structure consisting of 8 inputs, one hidden layer with 9 nodes represents the optimal final cost forecasting network. Finally, the best structure was tested on 15 samples randomly excluded from corresponding training sets. The test results showed the accuracy of neural networks in prediction.

Downloads

Published

2020-01-29

How to Cite

1.
Hassan B, Makkieh S, Titizian N. Forecasting the Final Cost of Infrastructure Projects in Syria Using Earned Value Management and Artificial Intelligence. Tuj-eng [Internet]. 2020Jan.29 [cited 2024Dec.26];42(1). Available from: https://journal.tishreen.edu.sy/index.php/engscnc/article/view/9395

Issue

Vol. 42 No. 1 (2020): Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series

Section

Articles

License

Copyright (c) 2020 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.

Most read articles by the same author(s)

1 2 > >>