Semnan University International Journal of Nonlinear Analysis and Applications 2008-6822 14 8 2023 08 01 Using support vector machine (SVM) technology to predict the duration of irrigation canal projects in western Iraq 73 81 7374 10.22075/ijnaa.2023.7374 EN Jumaa AL-Somaydaii Dams and Water Resources Department, University of Anbar, Ramadi, Iraq Aseel Abdaljader Dams and Water Resources Department, University of Anbar, Ramadi, Iraq Saadi Shartooh Sharqi Civil Engineering Department, University of Anbar, Ramadi, Iraq Nadhir Al Ansari Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, Sweden Journal Article 2022 11 17 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. https://ijnaa.semnan.ac.ir/article_7374_5c98a4e9cd7a35a3a506b3f9b2fc4bd9.pdf