Gabriella Orbán

21743650200

Publications - 4

Neural-network based modelling approach for loading systems

Gabriella Orbán Tibor Vadvári András Rövid P. Várlaki

Publication Name: International Conference on Emerging Trends in Engineering and Technology Icetet

Publication Date: 2011-12-01

Volume: Unknown

Issue: Unknown

Page Range: 72-76

Description:

As in many fields in modern logistics the system modelling and identification play an important role. By the modelling of complex non-linear systems different model approximation approaches are utilized. The approximation methods of mathematics are widely used in theory and practice for several problems. In the framework of the paper a higher order singular value decomposition (HOSVD) based approximation approach for neural network (NN) model approximation is introduced. The approach will be detailed from the point of view of logistic systems but it may be applicable for other fields, as well. The NNs in this case stand for local models based on which a more complex parameter varying model can numerically be reconstructed and reduced using the HOSVD. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/ICETET.2011.69

Control model for loading systems using higher order singular value decomposition

Gabriella Orbán András Rövid P. Várlaki

Publication Name: Proceedings 2011 IEEE International Conference on Computer Science and Automation Engineering Csae 2011

Publication Date: 2011-08-25

Volume: 3

Issue: Unknown

Page Range: 754-758

Description:

In this paper we present a method for constructing a control model of loading systems based on higher order singular decomposition (HOSVD) of a tensor. Modern logistics need control systems that are able to develop and improve the material and information flow by automating the control processes. We propose the application of linear parameter varying (LPV) structure by which non-linear systems can be controlled on the basis of linear control theories. Describing the system, modeling logistic processes require many uncertain input parameters. Using the proposed method the complexity of the model can be kept on a lower level. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/CSAE.2011.5952783

Effects of information technology investments on the efficiency of logistic processes

Gabriella Orbán

Publication Name: 14th World Congress on Intelligent Transport Systems ITS 2007

Publication Date: 2007-01-01

Volume: 7

Issue: Unknown

Page Range: 5238-5248

Description:

The output of logistics is performed by the appropriate and proportional use of material and information flows. Important issue is to determine the proper equilibrium between the resources devoted to the two main system elements. The necessity of continuous improvement of informatics and logistic flows is not questionable since the efficiency of logistics control systems can be increased by reducing the time gap between the time of gaining the data and use of information for planning purpose. In different logistics subsystems the role and importance of time gaps differ. Having generally overviewed the subsystems the papers introduce the efficiency of informatics based on Cobb-Douglas production function in order to spot the elements of logistics where the reduction of time gap is of economic interest, that is under what conditions can the IT developments and investment be efficient. Finally a draft framework is described as a general solution that can use informatic means in order to increase road transport system capacity usage.

Open Access: Yes

DOI: DOI not available

Takagi-sugeno fuzzy control models for large scale logistics systems

Gabriella Orbán István Harmati P. Várlaki

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-01-01

Volume: Unknown

Issue: Unknown

Page Range: 199-203

Description:

Requirements, such as adaptive behavior, learning ability and self regulative features, that have to be met by modern logistic systems, need the construction of such control systems that are able to control the basic processes and also to develop and improve the material and information system by automating the control processes. For controlling the logistical systems the papers propose the application of LPV structure by which non-linear systems can be controlled on the basis of linear control theories. The proposal points out that the priorities of different states are of great importance when generating the logical rules of operation. For resolving the difficulties of constructing mathematical algorithms fuzzy sets are suggested, so in the control model a Takagi-Sugeno solution is proposed, that can describe multi-input multi-output, non-linear, dynamic systems like logistical systems. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367389