Industrial Control System Based On Machine Learning SVM Algorithm - Hanane Zermane; Hayet Mouss; Djamel Touahar (University Of Eloued جامعة الوادي, 2020)
Machine learning is one of the most prominent signs of evolution and a mark of the marks of civilization in this century, as the latter immersed in many areas of life, it contributes to the improvement in smarter and faster ways. The idea of this work is based on use of machine learning to create an industrial supervision system that controls automatically a factory on real time mode as an alternative for the operators as possible as it is available. This work comes to highlight the importance of this learning in the field of industry as the main nerve of the econ-omy of many countries. It depends on the use of one of the tools of machine learning, which is SVM technique in an attempt to create an automatic control program for industrial systems of SCIMAT Company for cement production.
Intervention
Keywords: Industrial process; Supervision system; Machine Learning; Support Vector Ma-chine; Classification; Regression