Payame Noor University (PNU) Control and Optimization in Applied Mathematics 2383-3130 1 2 2016 12 01 Comparative Analysis of Machine Learning Algorithms with Optimization Purposes تحلیل تطبیقی الگوریتم‌های یادگیری ماشین با اهداف بهینه‌سازی 63 75 3399 EN Rohollah Alesheykh Payame Noor University Journal Article 2016 02 05 The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to optimize the precision of defect detection of concrete slabs depending on their qualitative evaluation‎. ‎Based on this idea‎, ‎some machine learning algorithms such as C4.5 decision tree‎, ‎RIPPER rule learning method and Bayesian network have been studied to explore the defect of concrete and to supply a decision system to speed up the defect detection process‎. ‎The results from the examinations show that the proposed RIPPER rule learning algorithm in combination with Fourier Transform feature extraction method could get a defect detection rate of 93% as compared to other machine learning algorithms. https://mathco.journals.pnu.ac.ir/article_3399_eac798a614b48609ebe90618f6dd2bca.pdf