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Found 5157 publications

Reconstruction of accidents involving commercial vehicles rollover

Gyula Kofalvi

Publication Name: European Automobile Engineers Cooperation 10th Eaec European Automotive Congress Eaec 2005

Publication Date: 2005-12-01

Volume: 3

Issue: Unknown

Page Range: 1056-1069

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Fuzzy rule interpolation for multidimensional input spaces with applications: A case study

T. D. Gedeon Domonkos Tikk L. T. Koczy Kok Wai Wong

Publication Name: IEEE Transactions on Fuzzy Systems

Publication Date: 2005-12-01

Volume: 13

Issue: 6

Page Range: 809-819

Description:

Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, this may result in a sparse fuzzy rule base. Fuzzy rule interpolation techniques have been established to solve the problems encountered in processing sparse fuzzy rule bases. In most engineering applications, the use of more than one input variable is common, however, the majority of the fuzzy rule interpolation techniques only present detailed analysis to one input variable case. This paper investigates characteristics of two selected fuzzy rule interpolation techniques for multidimensional input spaces and proposes an improved fuzzy rule interpolation technique to handle multidimensional input spaces. The three methods are compared by means of application examples in the field of petroleum engineering and mineral processing. The results show that the proposed fuzzy rule interpolation technique for multidimensional input spaces can be used in engineering applications. © 2005 IEEE.

Open Access: Yes

DOI: 10.1109/TFUZZ.2005.859316

Environmental influence on the fine structure of dummy-head HRTFs

András Illényi György Wersényi

Publication Name: Forum Acusticum Budapest 2005 4th European Congress on Acustics

Publication Date: 2005-12-01

Volume: Unknown

Issue: Unknown

Page Range: 2529-2534

Description:

The directional filtering of the outer ears is a significant step during the evaluation of spatial information. A computer-controlled dummy-head measurement system was developed to measure the HRTFs in huge amount and with increased spatial resolution. Effects and common properties of objects near the head (glasses, hair, baseball cap) were measured. Changes in the HRTFs due to the acoustical environment will be presented as function of frequency and azimuth for different elevations on 2D polar diagrams. Differences of about 1 dB are evaluated in the fine structure of the measured HRTFs and conclusions are drawn for the relevance of HRTF reproduction in binaural synthesis.

Open Access: Yes

DOI: DOI not available

An optimization model for maintenance of engineering structures

Kornélia Ambrus-Somogyi András Bakó

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 265-268

Description:

With the recognition that the engineering structures maintenance and repair needs far exceed the rescourses available to adress these needs, many firms have to turned to the development of ESMS (Enginnering Structures Management System) as a method to improve the allocation of these limited resources and the condition of their engineering structures. The paper provides an overviev of the need for ESMS. The concepts of level-of-service goals for functional adequacy, deterioration modeling and the relation of structural adequancy and optimization strategies for rescource allocation.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511584

Uncertainty representation in nonlinear and hybrid systems

P. Várlaki A. R. Várkonyi-Kóczy

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 313-318

Description:

Information of any kind always involve some kind of uncertainty, inaccuracy. The model used to represent the information during the information processing can affect the achievable preciseness and can determine the usability of different computing methods, as well. The data model must also be able to represent the uncertainty, inaccuracy of both the input data and the results. The two most popular data models for the representation of uncertain data are the "classical", probability based and the recently introduced fuzzy data model. With the increasing complexity of the computing problems and with the appearance and spreading of new modeling and computing techniques, the evaluation and representation of the uncertainty in different systems become an increasingly important question and methods for the mixed use of different data models can also be needed. This paper deals with the limits of the "classical", probability theory based uncertainty representation and examines possible solutions for information processing based on mixed data models together with different conversion methods between fuzzy and probability theory based representations.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511593

Fuzzy models, identification and applications

J. Botzheim L. T. Koczy

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 13-19

Description:

This paper gives a brief overview of fuzzy model identification techniques. The paper discusses how the membership functions of a fuzzy system can be extracted from an input/output data (pattern) set without human interference. There are several methods used for rule extraction known from the literature. The bacterial algorithm is an evolutionary technique that was inspired by the microbial evolution phenomenon. The Levenberg-Marquardt algorithm is an advanced gradient type optimization method that has been developed initially for neural networks and is introduced here for the optimization of the fuzzy rule base. Fuzzy clustering is presented also as another alternative way for the rule extraction. In the part describing the model the fuzzy rule interpolation method and the approach of hierarchical rule bases are introduced. Combining fuzzy rule interpolation with the use of hierarchically structured fuzzy rule bases leads to the reduction of the fuzzy algorithms' complexity. Hierarchical fuzzy modeling by clustering techniques is also introduced in the paper.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511538

An hybrid training method for B-spline neural networks

C. Cabrita J. Botzheim A. E. Ruano L. T. Koczy

Publication Name: 2005 IEEE International Workshop on Intelligent Signal Processing Proceedings

Publication Date: 2005-12-01

Volume: Unknown

Issue: Unknown

Page Range: 165-170

Description:

Current and past research has brought up new views related to the optimization of neural networks. For a fixed structure, second order methods are seen as the most promising. From previous works we have shown how second order methods are of easy applicability to a neural network. Namely, we have proved how the Levenberg-Marquard possesses not only better convergence but how it can assure the convergence to a local minima. However, as any gradient-based method, the results obtained depend on the startup point. In this work, a reformulated Evolutionary algorithm - the Bacterial Programming for Levenberg-Marquardt is proposed, as an heuristic which can be used to determine the most suitable starting points, therefore achieving, in most cases, the global optimum. © 2005 IEEE.

Open Access: Yes

DOI: DOI not available

Implicit extension of Taylor series method with numerical derivatives for initial value problems

G. Molnárka E. Miletics

Publication Name: Computers and Mathematics with Applications

Publication Date: 2005-10-01

Volume: 50

Issue: 7

Page Range: 1167-1177

Description:

The Taylor series method is one of the earliest analytic-numeric algorithms for approximate solution of initial value problems for ordinary differential equations. The main idea of the rehabilitation of this algorithms is based on the approximate calculation of higher derivatives using well-known finite-difference technique for the partial differential equations. The approximate solution is given as a piecewise polynomial function defined on the subintervals of the whole interval integration. This property offers different facility for adaptive error control. This paper describes several explicit Taylor series algorithms with numerical derivatives and their implicit extension and examines its consistency and stability properties. The implicit extension based on a collocation term added to the explicit truncated Taylor series and the approximate solution obtained as a continuously differentiable piecewise polynomials function. Some numerical test results is presented to prove the efficiency of these new-old algorithm. © 2005 Elsevier Ltd. All rights reserved.

Open Access: Yes

DOI: 10.1016/j.camwa.2005.08.017

Fuzzy pseudo-thesaurus based clustering of a folkloristic corpus

T. D. Gedeon L. T. Koczy S. Szaszkó

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2005-09-01

Volume: Unknown

Issue: Unknown

Page Range: 126-131

Description:

Automatic thesaurus extraction is essential for modern information retrieval. We develop a method for fuzzy pseudo-thesaurus based on word pair co-occurrence in documents. In this study it is presented, that considering the Word Frequency Degree counted on the whole corpus makes the obtained pseudo-thesaurus usable. Such parameters were found with which most of the obtained pairs of words were validated to be related by human expert. Among the extracted pairs and groups of words the relationship is often looser than synonymy, but they identify the frequently repeated topics of the corpus. We suggest the use of groups of closely related words for the definition of different topics and based on this clustering of the documents were performed.1 © 2005 IEEE.

Open Access: Yes

DOI: DOI not available