A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS
In this article, a new method for complexity determination by using fractals in combination with an artificial intelligent approach is proposed and its application in laser hardening technology is detailed. In particular, nanoindentation tests were applied as a way to investigate the hardness proper...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Center for Quality, Faculty of Engineering, University of Kragujevac, Serbia
2020-09-01
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| Series: | International Journal for Quality Research |
| Subjects: | |
| Online Access: | http://ijqr.net/journal/v14-n3/4.pdf |
| _version_ | 1818562948283498496 |
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| author | Matej Babič Cristiano Fragassa Grzegorz Lesiuk Dragan Marinković |
| author_facet | Matej Babič Cristiano Fragassa Grzegorz Lesiuk Dragan Marinković |
| author_sort | Matej Babič |
| collection | DOAJ |
| description | In this article, a new method for complexity determination by using fractals in combination with an artificial intelligent approach is proposed and its application in laser hardening technology is detailed. In particular, nanoindentation tests were applied as a way to investigate the hardness properties of tool steel alloys with respect to both marginal and relevant changes in laser hardening parameters. Specifically, process duration and temperature were considered, together with nanoindentation, later related to surface characteristics by image analysis and Hurst exponent determination. Three different Machine Learning algorithms (Random Forest, Support Vector Machine and k-Nearest Neighbors) were used and predictions compared with measures in terms of mean, variability and linear correlation. Evidences confirmed the general applicability of this method, based on integrating fractals for microstructure analysis and machine learning for their deep understanding, in material science and process engineering. |
| first_indexed | 2024-12-14T01:10:25Z |
| format | Article |
| id | doaj.art-f254e47aa56045359b987dd4a39ac34b |
| institution | Directory Open Access Journal |
| issn | 1800-6450 1800-7473 |
| language | English |
| last_indexed | 2024-12-14T01:10:25Z |
| publishDate | 2020-09-01 |
| publisher | Center for Quality, Faculty of Engineering, University of Kragujevac, Serbia |
| record_format | Article |
| series | International Journal for Quality Research |
| spelling | doaj.art-f254e47aa56045359b987dd4a39ac34b2022-12-21T23:22:46ZengCenter for Quality, Faculty of Engineering, University of Kragujevac, SerbiaInternational Journal for Quality Research1800-64501800-74732020-09-0114370571610.24874/IJQR14.03-04A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICSMatej Babič0https://orcid.org/0000-0002-5446-5087Cristiano Fragassa1https://orcid.org/0000-0003-0046-8810Grzegorz Lesiuk2https://orcid.org/0000-0003-3553-6107Dragan Marinković3https://orcid.org/0000-0002-3583-9434Faculty of Information Science in Novo Mesto, Novo Mesto, SloveniaAlma Mater Studiorum University of Bologna Bologna, ItalyWroclaw University of Science and Technology, Wrocław; PolandTechnical University Berlin Berlin, GermanyIn this article, a new method for complexity determination by using fractals in combination with an artificial intelligent approach is proposed and its application in laser hardening technology is detailed. In particular, nanoindentation tests were applied as a way to investigate the hardness properties of tool steel alloys with respect to both marginal and relevant changes in laser hardening parameters. Specifically, process duration and temperature were considered, together with nanoindentation, later related to surface characteristics by image analysis and Hurst exponent determination. Three different Machine Learning algorithms (Random Forest, Support Vector Machine and k-Nearest Neighbors) were used and predictions compared with measures in terms of mean, variability and linear correlation. Evidences confirmed the general applicability of this method, based on integrating fractals for microstructure analysis and machine learning for their deep understanding, in material science and process engineering.http://ijqr.net/journal/v14-n3/4.pdffractalscomplexitymachine learninglaser hardeningsurface quality |
| spellingShingle | Matej Babič Cristiano Fragassa Grzegorz Lesiuk Dragan Marinković A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS International Journal for Quality Research fractals complexity machine learning laser hardening surface quality |
| title | A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS |
| title_full | A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS |
| title_fullStr | A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS |
| title_full_unstemmed | A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS |
| title_short | A NEW METHOD FOR COMPLEXITY DETERMINATION BY USING FRACTALS AND ITS APPLICATIONS IN MATERIAL SURFACE CHARACTERISTICS |
| title_sort | new method for complexity determination by using fractals and its applications in material surface characteristics |
| topic | fractals complexity machine learning laser hardening surface quality |
| url | http://ijqr.net/journal/v14-n3/4.pdf |
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