ttp://iaeme.com/Home/journal/IJCIET 5 editor@iaeme.com h International Journal of Civil Engineering and Technology (IJCIET) Volume 12, Issue 3, March 2021, pp. 5-22, Article ID: IJCIET_12_03_002 Available online at ttp://iaeme.com/Home/issue/IJCIET?Volume=12&Issue=3 h Journal Impact Factor (2020 11.3296 (Calculated by GISI) www.jifactor.com ): ISSN Print: 0976-6308 and ISSN Online: 0976-6316 DOI: 10.34218/IJCIET.12.3.2021.002 © IAEME Publication Scope Database Indexed USING SUPPORT VECTOR MACHINE (SVM) FOR TIME AND COST OVERRUN ANALYSIS IN CONSTRUCTION PROJECTS IN EGYPT Mohamed Gamal Eltoukhy Department of Civil Engineering, Construction management, German University in Cairo, Egypt Ayman H. Nassar Department of Civil Engineering, Construction management, German University in Cairo, Egypt ABSTRACT This study aims to model construction projects cost and time overruns, with the specific objectives of identifying the causes and effects of cost and schedule overruns in construction projects. This is because the concept of construction projects cost and schedule overruns has attracted much attention in recent years and that researchers and research bodies, be it corporate or government that try to formulate remedies to projects cost and schedule overruns should begin with an understanding of the causes of these overruns and their effects to the construction industry as a whole. Since, time and cost performance are the fundamental criteria for success of any project. The project management technique for tracking the most critical factors that affect the pr tools and developed oject’s overruns of planned schedule and planned budget using software are helpful in comparing the project with stipulated time and cost. This research investigates ranking factors from two questionnaires to compute the severity index among various construction projects and ranked each factor according to the percentages of each factor occurrence. Two models constructed using Linear regression (LR) and machine learning (Support Vector Machine) is one of the artificial intelligence systems to fit the given data for all construction projects. First model is developed for time overrun prediction with high accuracy and second model is developed for cost overrun for various construction projects. Check the performance and accuracy of the predicting model by some certain projects of time and cost projects data and check the variation of the results between the actual results and predicted results. Keywords: Schedule overruns, Cost overruns, Construction Industry, Project management, Causes and effect of cost and schedule overruns, Contractor, Owner, Consultant, Machine learning, Artificial intelligence, Support Vector Machine (SVM)