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2019 | OriginalPaper | Buchkapitel

New Method of Sequences Spiral Hybrid Using Machine Learning Systems and Its Application to Engineering

verfasst von : Matej Babič, Isak Karabegović, Sanda Ipšič Martinčič, Gyula Varga

Erschienen in: New Technologies, Development and Application

Verlag: Springer International Publishing

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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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Metadaten
Titel
New Method of Sequences Spiral Hybrid Using Machine Learning Systems and Its Application to Engineering
verfasst von
Matej Babič
Isak Karabegović
Sanda Ipšič Martinčič
Gyula Varga
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-319-90893-9_28

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