- author = "Matej Babic",
- title = "Analiza kaljenih materialov s pomocjo fraktalne geometrije",
- alternate_title = "Analysis of Hardened Materials Using Fractal Geometry",
- school = "Racunalnistvo in Informatiko, Fakulteta za Elektrotehniko, Univerza v Mariboru",
- year = "2014",
- address = "Maribor",
- keywords = "genetic algorithms, genetic programming, inteligentni sistemi, algoritmi, hibridni sistemi, strojno ucenje, fraktalna geometrija, teorija grafov, topografija materiala po toplotni obdelavi, intelligent system, algorithms, hybrid system, machine learning, ANN, fractal geometry, graph theory, topography of materials after heat treatment",
-
URL = "
https://dk.um.si/IzpisGradiva.php?id=46366&lang=eng&prip=rul:10960417:d1",
-
URL = "https://dk.um.si/Dokument.php?id=67818&lang=eng",
-
URL = "
https://core.ac.uk/download/pdf/67581852.pdf",
-
URL = "https://www.proquest.com/docview/2194811728",
- size = "178 pages",
-
abstract = "In this dissertation we study intelligent systems and
the search for knowledge, computing paradigms that are
useful and beneficial for the heat treatment of
materials. To identify the complexity of different
heat-treated samples, we used the fractal geometry
method. We designed an intelligent system through which
we announced topographical properties of the material
after heat treatment. We have also developed a new
algorithm for 3D graph visibility. With the help of the
topological properties density of 3D graphs, we have
built an intelligent system which can predict the
topographic characteristics of the samples after heat
treatment. Fractal geometry can be used to analyse
complex structures that occur in the heat treatment of
materials. Thus, the use of fractal geometry
demonstrates the advantages of laser heat treatment
techniques over the inductive, classical and the
hardening furnace. Fractal geometry is a new approach,
based on the characterisation of irregular
microstructures, and serves as an assessment tool for
determining structural properties. It can be used in
the analysis of different heattreated materials.
Fractal geometry is based on the idea of invariant
magnification, which means that the observed image is
not the same regardless of how strong the microscope
is. It should be noted that the fractal dimension does
not fully characterise the geometry, but is rather an
indication of irregularities. Fractal geometry was used
here to determine the topographical properties of
hardened materials . We have introduced a new method
for calculating the fractal dimension of a 3D object.
With the development of laser technology in the field
of heat treatment of materials there is an increased
need to develop new methods with which to determine
(set) better resistance of material, lower friction and
better heat resistance of material. We therefore aim to
build intelligent systems to increase productivity in
the field of heat treatment of materials. With the help
of the intelligent system we intend to show which
technique of heat treatment is best. In this
dissertation we present four new composite hybrid
methods:
* composite hybrid genetic algorithms - multiple regression - neural network-multiple regression (we call it a hybrid loop).
* composite hybrid genetic algorithm - neural network - multiple regression- neural network (we call it the optimal hybrid loop).
* composite hybrid genetic algorithm - neural network - multiple regression-neural network - multiple regression (we call it the cyclic hybrid).
* composite hybrid genetic algorithm - multiple regression - neural network -multiple regression - neural network (we call it the optimal linear hybrid).
Composite hybrid performances were slightly worse than expected, because of the shortcomings of the individual basic methods. The multiple regression method is the worst method and adversely affected the composite hybrid. The new composite hybrids give better results than existing composite hybrid systems, however.
We want to improofe results of new hybrid system, thus we built new composite hybrib, hyiper hybrid.
At the end of the dissertation further comments are made and a two new hybrid systems proposed which we call the spiral hybrid and optimal spiral hybrid. This method are useful when a large number of basic methods are employed. We also propose combining (pooling) the six new hybrid methods presented in the new hyper hybrids.",
-
notes = "Solvenian
https://books.google.co.uk/books/about/Hybrid_System_of_Machine_Learning_Using.html?id=dBZ3zQEACAAJ Hybrid System of Machine Learning Using Genetic Programming and Multiple Regression
Supervisor: Peter Kokol",
