Abstract
In an era of increased emphasis on sustainability and quality assurance, knowledge about metals and other materials used in products, manufacturing processes, and construction is invaluable. Metallurgy is the study of the physical and chemical behaviour of metallic elements. CNC operators typically test many materials with different CNC machine parameters to optimize the topological properties of materials. In this article we present a solution to this problems. We analyse SEM pictures of the microstructure of robot laser hardened specimens using graph theory and fractal geometry. Intelligent systems methods enable predictions for mechanical engineering based on a hybrid of genetic programming and multiple regression, with applications to metallurgy and mechanical engineering. Hybrid evolutionary computation is a generic, flexible, robust, and versatile method for solving complex global optimisation problems that can also be used in practical applications. Hybrid intelligent systems enhance laser hardening by decreasing the process time and increasing the topographical properties of materials.
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Project no. NKFI-125117 has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the K_17 funding scheme.
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Babič, M., Karabegović, I., Martinčič, S.I., Varga, G. (2019). New Method of Sequences Spiral Hybrid Using Machine Learning Systems and Its Application to Engineering. In: Karabegović, I. (eds) New Technologies, Development and Application. NT 2018. Lecture Notes in Networks and Systems, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-90893-9_28
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DOI: https://doi.org/10.1007/978-3-319-90893-9_28
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