CONSTRUCTION MATERIALS OBTAINED BY RECYCLING ASH FROM COAL-FIRED POWER PLANTS ASH PONDS. ESTIMATION OF BASIC MECHANICAL PROPERTIES BY MEANS OF MACHINE LEARNING ALGORITHMS. PART II – MACHINE LEARNING ALGORITHMS BENCHMARKING.

Autor:	Anghelescu, Lucica, Diaconu, Bogdan, Cruceru, Mihai, Gueorguiev, Tzvetelin K.
Předmět:	MACHINE learning ASH (Tree) CONSTRUCTION materials POWER plants PETROLEUM waste COAL-fired power plants PONDS WASTE recycling
Zdroj:	Annals of 'Constantin Brancusi' University of Targu-Jiu. Engineering Series / Analele Universităţii Constantin Brâncuşi din Târgu-Jiu. Seria Inginerie; 2022, Issue 2, p37-47, 11p
Abstrakt:	It is a fact that engineering properties of the building materials are particularly difficult to model analytically. Given the importance of their values in any application, it is critical to have an estimation of every engineering parameter that is required. This two-part paper will present a dataset containing three engineering properties of some new materials obtained through recycling waste from petroleum industry and from coal-based power. The second part of the paper will present the application of several Machine Learning algorithms to the dataset mentioned above. The performance of each model was assessed and discussed. It was found that Bagging (with a Decision Tree based algorithm) and XGBoost algorithm have the best performance. [ABSTRACT FROM AUTHOR]
Databáze:	Supplemental Index
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