AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

Mathematics

Marius Fișcă¹  Vlad Mureșan¹  Iulia Clitan¹  Mihail Abrudean¹  Honoriu Vălean¹  Roxana Motorga¹  Emilian Ceuca²  Mihaela-Ligia Ungureșan³ 

[1] Automation Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania;Informatics, Mathematics and Electronics Department, “1 Decembrie 1918” University of Alba Iulia, 510009 Alba Iulia, Romania;Physics and Chemistry Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania;

关键词: separation cascade;    modeling;    efficiency;    AI (artificial intelligence);    neural network;    ¹⁸O isotope;   

DOI  :  10.3390/math9233088

来源: DOAJ

【 摘 要 】

In the paper, the comparison between the efficiency of using artificial intelligence methods and the efficiency of using classical methods in modelling the industrial processes is made, considering as a case study the separation process of the ¹⁸O isotope. Firstly, the behavior of the considered isotopic separation process is learned using neural networks. The comparison between the efficiency of these methods is highlighted by the simulations of the process model, using the mentioned modelling techniques. In this context, the final part of the paper presents the proposed model being simulated in different scenarios that can occur in practice, thus resulting in some interesting interpretations and conclusions. The paper proves the feasibility of using artificial intelligence methods for industrial processes modeling; the obtained models being intended for use in designing automatic control systems.

【 授权许可】

Unknown