Using support vector machine (SVM) technology to predict the duration of irrigation canal projects in western Iraq

Document Type : Research Paper


1 Dams and Water Resources Department, University of Anbar, Ramadi, Iraq

2 Civil Engineering Department, University of Anbar, Ramadi, Iraq

3 Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, Sweden


In this study, a support vector machine (SVM) based technique for timing irrigation projects is presented, and one of the most accurate predictive models in calculating the final project duration within the contract documents, where the research problem is projects are not completed within the contract period because most of the total project duration is determined In an unthoughtful manner by the employer. Linear regression models were applied to data and information for several projects, and a significant improvement in forecast accuracy was obtained.


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Volume 14, Issue 8
August 2023
Pages 73-81
  • Receive Date: 17 November 2022
  • Revise Date: 10 January 2023
  • Accept Date: 22 January 2023
  • First Publish Date: 28 January 2023