Thesis supervisor: Imre Kocsis
Location of studies (in Hungarian): Debreceni Egyetem Informatikai Kar Abbreviation of location of studies: DE IK
Description of the research topic:
Nowadays engineering design, production, and maintenance are supported by effective software, the calculations related to the algorithms and mathematical methods applied are carried out by these software. Thus the majority of engineering tasks belong to the specification, analysis and evaluation of systems and processes.
Decreasing time-demand of calculations enables us to gather and analyse large amounts of input and output data and to investigate the connection between these data in order to find optimum design, production and maintenance parameters and to enhance the effectiveness of design and process control.
The complexity of connection between input and output data of technical systems requires new approaches and flexible methods. According to the publications in this area, the application of the machine learning techniques (e.g. neural networks, support vector machines) can be an effective way to the system analysis.
Integration of certain analysing methods and algorithms in a software can result in a useful supporting tool for engineering design and optimization.
Bibliography:
Haykin, S., Neural Networks and Learning Machines, Prentice Hall, 2008
Smola, A.J., Schölkopf, B., A Tutorial on Support Vector Regression (in: Statistics and Computing 14.3 (2004)
Zeigler, Phillip: Theory of modelling and simulation, Academic Press, 2000.
Horváth I., et al: Advanced Design Support, Delft University of Technology, 2005.
Stoll, H.W.: Product design methods and practices, Marcel Dekker, Inc., 1999.
Soares, C.A.M.: Computer Aided Optimal Design: Structural and Mechanical Systems, Springer-Verlag, 1987.
Sydenham, P. H.: Handbook of Measurement Science, Vol. 1 and 2., J. Wiley 1982.
Bathe, K. J. Finite Element Procedures. 1996 Prentice Hall, Simon & Schuster / A Viacom Company, Upper Saddle River, New Jersey
Girod, Rabenstein, Stenger, Signals and Systems, Wiley, 2000
Recommended language skills (in Hungarian): angol Number of students who can be accepted: 1
Deadline for application: 2018-02-16
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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