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

6Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

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 Lecture Notes in Networks and Systems (Vol. 42, pp. 227–237). Springer. https://doi.org/10.1007/978-3-319-90893-9_28

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free