- author = "Matej Babic",
- title = "A new hybrid-system method of Machine Learning using a new method of fractal geometry and a new method of graph theory",
- journal = "Elektrotehniski vestnik",
- year = "2016",
- volume = "83",
- number = "1-2",
- pages = "42--46",
- keywords = "genetic algorithms, genetic programming, image processing, intelligent system, visibility graphs, fractal dimension",
- ISSN = "0013-5852",
-
URL = "
https://ev.fe.uni-lj.si/1-2-2016/Babic.pdf",
-
URL = "
https://ev.fe.uni-lj.si/online.php?vol=83",
-
URL = "https://www.proquest.com/docview/1789072317?sourcetype=Scholarly%20Journals",
- size = "5 pages",
- abstract = "a hybrid system method to predict the volume of the robot-laser-hardened specimens when one of the parameters in the existing model cannot be measured or calculated the intelligent-system is presented. Also, we have a model of the intelligent system to predict the volume of hardened specimens developed by someone, but we can not calculate one parameter in it. Thus, we develop a new method of the hybrid intelligent system to solve this problem. We develop a hybrid of genetic programming and multiple regression. To predict the volume of hardened specimens, we use teh neural network, genetic algorithm and multiple regression. The genetic programming modelling results show a good agreement with the measured volume of hardened specimens. We analyse the SEM picture of the microstructure of robot-laser-hardened specimens with a mathematical method. In this open problem we use the graph theory and fractal geometry. Fractal dimensions are calculated using image processing of a SEM micrographs in combination with a box-counting algorithm using ImageJ software.",
-
notes = "cites \cite{Babic:thesis}
Jozef Stefan Institute, Slovenia",
