The Application of tree-based ML algorithm in steel plates Ffaults identification

Abstract

In the production of steel plates, it is essential to detect the surface quality effectively in real time. If the faults are not identi ied quickly and correctly, and the production technology is not corrected in time, the production of such faulty steel plates will cause huge economic losses to the company. In the traditional manufacturing process, the manual detection methods are often used to identify these faults, which is inef icient, inaccurate and timeconsuming. Steel plate fault classi ication can be regarded as a typical classi ication problem in machine learning ields, which can be conducted more ef iciently, quickly and accurately with the help of ef icient algorithm. Rapid classi ication of faults allows operators to ind issues more easily and improve the production processes. We apply a series of classical machine learning algorithms based on decision trees (Decision Tree, Adaboosting, Bagging, Random Forest) to verify the ten fold cross-validation of the steel plate fault data. It is found that Bagging algorithm outperforms the other methods and achieves 96.30% and 90% accuracy on the training and testing set, respectively. This will allow us to ind abnormalities on the surface of the steel plate timely and reduce losses. Based on these algorithms, we can cooperate with iron and steel practitioners to design more appropriate algorithms to achieve higher recognition accuracy in the future.

From Politics of Islam to Terrorism: Discovering the Roots of Islamophobia in Indonesia

“…Several incidents involved FPI, such as the conflict in Ketapang, Jakarta, and attacks on entertainment venues, food stalls, and houses of worship, particularly churches and the National Commission on Human Rights (Komnas HAM) office. FPI also actively participated in political and cultural activism, such as the rejection of the beauty queen in Jakarta, the disclaimer of the appointment of Governor Ahok to replace Jokowi, and resistance towards the Jokowi government (Nathaniel, 2019;Chen, 2018;El-Den et al, 2017). Such a situation provokes Islamophobia in society, particularly from the Christians to the militant groups.…”

Çelik Levha Arıza Tespiti için Makine Öğrenimi Algoritmalarının Karşılaştırmalı Analizi

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