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Found 6273 publications

Nonlinear simulation of a nondestructive testing measurement system

Amália Iványi Miklós Kuczmann

Publication Name: Physica B Condensed Matter

Publication Date: 2006-02-01

Volume: 372

Issue: 1-2

Page Range: 373-377

Description:

A nondestructive testing (NDT) equipment has been fabricated. The description of the measurement set-up with some measured crack signals applying a Hall-type sensor, furthermore, the T,Ψ-Ψ potential formulation of the nonlinear eddy current field problem in the time domain can be found in this paper. The hysteresis characteristic of the material has been simulated by the previously developed neural network (NN) based isotropic vector hysteresis model. The nonlinear system of equations has been solved by the fixed-point iteration scheme via the polarization method. Comparisons between the results of the 3D simulations and the measurements are also presented. © 2005 Elsevier B.V. All rights reserved.

Open Access: Yes

DOI: 10.1016/j.physb.2005.10.115

Anisotropic vector hysteresis model applying Everett function and neural network

Amália Iványi Miklós Kuczmann

Publication Name: Physica B Condensed Matter

Publication Date: 2006-02-01

Volume: 372

Issue: 1-2

Page Range: 138-142

Description:

This paper deals with a simulation technique based on neural networks and an identification method to approximate the behavior of vector hysteresis characteristics of ferromagnetic materials. The identification procedure is based on theoretical measured vector Everett functions using Fourier expansion to deal with angle dependence of the measured scalar Everett functions and of the vector Everett functions in the 2D or in the 3D space. Computing afterwards the theoretical measured vector Everett functions for some given directions, the corresponding hysteresis models are approximated by neural networks and are used to build up the vectorial hysteresis model both in isotropic and anisotropic case. The properties of the anisotropic model has been analyzed and shown in figures. For some examples, the first order reversal curves determined from the vectorial model are compared with the corresponding measured curves that have been used to compute the measured scalar Everett functions being the input for the identification procedure. © 2005 Elsevier B.V. All rights reserved.

Open Access: Yes

DOI: 10.1016/j.physb.2005.10.034

Bacterial memetic algorithm for fuzzy rule base optimization

Cristiano Cabrita János Botzheim Tamás D. Gedeon Carlos Fonseca António E. Ruano László T. Kóczy

Publication Name: 2006 World Automation Congress Wac 06

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The LevenbergMarquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques - the bacterial memetic algorithm - was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule extraction. The new method can optimize not only the rules, but can also find the optimal size of the rule base. Copyright - World Automation Congress (WAC) 2006.

Open Access: Yes

DOI: 10.1109/WAC.2006.376057

Convergence of the key algorithm of traffic-flow analysis

László Muka Gábor Lencse

Publication Name: Journal of Computing and Information Technology

Publication Date: 2006-01-01

Volume: 14

Issue: 2

Page Range: 133-139

Description:

The traffic-flow analysis (TFA) [1] is a novel method for the performance estimation of communication systems. TFA is a combination of simulation and numerical methods. In the first step, TFA distributes the traffic in units of properly chosen size using the actual routing algorithm of the network. In the second step, TFA adjusts the time distribution of the traffic according to the finite capacities of the network. The convergence of the algorithm used in the second step of TFA is proven in this paper. The speed of convergence is also examined.

Open Access: Yes

DOI: 10.2498/cit.2006.02.04

Generalised weighted relevance aggregation operators for hierarchical fuzzy signatures

János Botzheim B. Sumudu U. Mendis Tamás D. Gedeon László T. Kóczy

Publication Name: Cimca 2006 International Conference on Computational Intelligence for Modelling Control and Automation Jointly with Iawtic 2006 International Conference on Intelligent Agents Web Technologies

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical Fuzzy Signature Structures. In this paper, we further generalise the weights and the aggregation into a new operator called Weighted Relevance Aggregation Operator (WRAO). WRAO enhances the adaptability of the fuzzy signature model to different applications and simplifies the learning of fuzzy signature models from data. We also show the methodology of learning these aggregation operators from data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/CIMCA.2006.110

Classification of time series via wavelet subband analysis using support vector machine classifier

B. Benyo Béla Paláncz

Publication Name: Periodica Polytechnica Electrical Engineering

Publication Date: 2006-01-01

Volume: 50

Issue: 1-2

Page Range: 129-140

Description:

An improved feature extraction method has been developed for classification and identification of time series, in case of the number of the experiments are considerably less than that of the samples in time series. The method based on the subband analysis of the wavelet transformation of the time signals, provides lower dimension feature vectors as well as much more robust kernel-based classifier than the traditional wavelet-based feature extraction method does. The application of this technique is illustrated by the classification of cerebral blood flow oscillation using support vector classifier with Gaussian kernel. The computations were carried out with Mathematica 5.1 and its Wavelet Application.

Open Access: Yes

DOI: DOI not available

Expanded scope of traffic-flow analysis: Entity flow-phase analysis for rapid performance evaluation of enterprise process systems

László Muka Gábor Lencse

Publication Name: Esm 2006 2006 European Simulation and Modelling Conference Modelling and Simulation 2006

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: 94-98

Description:

This paper describes entity-flow phase analysis (EFA) which is a method for fast performance analysis of organisational process systems. EFA, similarly to traffic-flow analysis for communication systems (TFA), uses the combined approach of simulation and numerical methods. In simulation projects initiated to support the design of Information and Communication Technology (ICT) system and Business Process (BP) system in an organisation the parallel analysis of different systems may be efficient. EFA is a promising evaluation method to be applied for systems with determined BP and ICT subsystems in an organisational environment.

Open Access: Yes

DOI: DOI not available

Fuzziness and computational intelligence: Dealing with complexity and accuracy

László T. Kóczy

Publication Name: Soft Computing

Publication Date: 2006-01-01

Volume: 10

Issue: 2

Page Range: 178-184

Description:

No description provided

Open Access: Yes

DOI: 10.1007/s00500-005-0470-3

Laser powder deposition of tool steels: Strategies leading to homogeneous parts

Lino Costa Tamás Réti R. Vilar

Publication Name: Materials Science Forum

Publication Date: 2006-01-01

Volume: 514-516

Issue: PART 1

Page Range: 739-743

Description:

The microstructure and properties of tool steel parts built by laser powder deposition (LPD) depend considerably on the build-up strategy and on the processing parameters used. This dependence can lead to inconsistent results which may limit the widespread acceptance of LPD. There is, thus, a need for efficient process optimisation tools that take into consideration the complex phase transformations that may occur during the part build-up process and their effect on final properties. A model coupling finite element heat transfer calculations with transformation kinetic theory has been developed, which allows the microstructure and property distributions in parts produced by LPD to be predicted. Application of this model to the deposition of tool steels not only explains the origin of the heterogeneous distribution of properties usually mentioned in the literature but also allows designing build-up strategies that consistently lead to homogeneous, high quality parts. Its application to the study of the influence of substrate pre-heating and idle time between the deposition of consecutive layers is illustrated in the present paper.

Open Access: Yes

DOI: 10.4028/www.scientific.net/msf.514-516.739