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Function approximation performance of Fuzzy Neural Networks based on frequently used fuzzy operations and a pair of new trigonometric norms

László Gál Rita Lovassy László T. Kóczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

A new triangular t-norm and t-conorm are presented. The new fuzzy operations combined with the standard negation are applied in a practical problem, namely, they are proposed as suitable triangular norms for defining a fuzzy flip-flop based neuron. Other fuzzy J-K and D flip-flop based neurons are constructed by using algebraic, Lukasiewicz, Yager, Dombi and Hamacher connectives. The function approximation performance of a Fuzzy Neural Networks (FNN) built up from various fuzzy neurons are evaluated using six increasingly more complicated problems: various sine waves, battery cell charging characteristics, two dimensional trigonometric functions and a six dimensional benchmark problem. It is shown that the new norms lead to FNNs with better approximation properties in some cases than all the previous ones. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584252

Hierarchical fuzzy system modeling by genetic and bacterial programming approaches

János Botzheim Krisztián Balázs László T. Kóczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper a method is proposed for constructing hierarchical fuzzy rule bases in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The resultant hierarchical rule base is the knowledge base, which is constructed by using structure constructing evolutionary techniques, namely, Genetic and Bacterial Programming Algorithms. Applying hierarchical fuzzy rule bases is a way of reducing the complexity of the knowledge base, whereas evolutionary methods ensure a relatively efficient learning process. This is the reason of the investigation of this combination. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584220

Decision making in multi-robot cooperation by fuzzy signature sets

Áron Ballagi László T. Kóczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper presents some examples for fuzzy communication and intention guessing from the real life to the cooperation of intelligent mobile robots. In a special experimental environment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584821

The effect of 1-MCP and its preservative solution combinations on the vase life of rose cultivar 'Bordeaux'

G. Boronkay E. Jámbor-Benczúr O. Terék Á Máthé

Publication Name: Acta Horticulturae

Publication Date: 2010-11-11

Volume: 877

Issue: Unknown

Page Range: 291-296

Description:

The effect of 1-MCP on rose cultivar 'Bordeaux' was studied in the case of different preservative solutions. The flowers were treated with 1-MCP for 6 hours at 17°C and for 18 hours on 4°C. The diameter of flowers and the vase life proved to be better with the treatment of 18 hours. The best result was achieved, when the flowers were treated with 1-MCP (18 hours) in Spring solution. In this case 11,2 days was the vase life compared to control 8,25 days, that way the vase life was extended with 3 days.

Open Access: Yes

DOI: 10.17660/ActaHortic.2010.877.34

Effect of different treatments on vase life of carnation 'Gioko'

E. Jámbor-Benczúr F. A. Hassan I. Mosonyi O. Terék Á Máthé

Publication Name: Acta Horticulturae

Publication Date: 2010-11-11

Volume: 877

Issue: Unknown

Page Range: 1757-1762

Description:

The effect of 1-MCP combined with Clorox and sucrose was studied. Cut flowers of Dianthus caryophyllus 'Gioko' were treated with 1-MCP 0.5 g m -3 for 6 hours at 20°C. Clorox in 2 ml L-1 and sucrose 10-50 g L-1 concentration was added. The treatments with 1-MCP increased the vase life with 5 days, and the sucrose in low concentrations improved the ornamental quality of the flowers. The SPAD values increased till the 6th day. The 1-MCP treatments gave much better results compared to the control and Spring as well, and it seems to be possible to replace Spring with 1-MCP treatment.

Open Access: Yes

DOI: 10.17660/ActaHortic.2010.877.241

Large scale simulations of the euler equations on GPU clusters

Manfred Liebmann Craig C. Douglas Zoltán Horváth Gundolf Haase

Publication Name: Proceedings 9th International Symposium on Distributed Computing and Applications to Business Engineering and Science Dcabes 2010

Publication Date: 2010-11-05

Volume: Unknown

Issue: Unknown

Page Range: 50-54

Description:

The paper investigates the scalability of a parallel Euler solver, using the Vijayasundaram method, on a GPU cluster with 32 Nvidia Geforce GTX 295 boards. The aim of this research is to enable large scale fluid dynamics simulations with up to one billion elements. We investigate communication protocols for the GPU cluster to compensate for the slow Gigabit Ethernet network between the GPU compute nodes and to maintain overall efficiency. A diesel engine intake-port and a nozzle, meshed in different resolutions, give good real world examples for the scalability tests on the GPU cluster. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/DCABES.2010.17

Optimization in fuzzy flip-flop neural networks

László Gál Rita Lovassy László T. Kóczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 337-348

Description:

The fuzzy J-K and D flip-flops present s-shape transfer characteristics in same particular cases. We propose the fuzzy flip-flop neurons; single input-single output units derived from fuzzy flip-flops as sigmoid function generators. The fuzzy neurons-based neural networks, Fuzzy Flip-Flop Neural Networks (FNN) parameters are quasi optimized using a second-order gradient algorithm, the Levenberg-Marquardt method (LM) and an evolutionary algorithm, the Bacterial Memetic Algorithm with Modified Operator Execution Order (BMAM). The quasi optimized FNN's performance based on Dombi and Yager fuzzy operations has been examined with a series of test functions. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_27

Some examples of computing the possibilistic correlation coefficient from joint possibility distributions

József Mezei Peter Varlaki Robert Fuller

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 153-170

Description:

In this paper we will show some examples for computing the possibilistic correlation coefficient between marginal distributions of a joint possibility distribution. First we consider joint possibility distributions, (1-x-y), (1-x 2-y 2), and (1-x 2-y) on the set {(x,y)≡R2| x≥0,y≥0,x+y≤1}, then we will show (i) how the possibilistic correlation coefficient of two linear marginal possibility distributions changes from zero to -1/2, and from -1/2 to -3/5 by taking out bigger and bigger parts from the level sets of a their joint possibility distribution; (ii) how to compute the autocorrelation coefficient of fuzzy time series with linear fuzzy data. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_13

Comparative investigation of various evolutionary and memetic algorithms

János Botzheim Krisztián Balázs László T. Kóczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 129-140

Description:

Optimization methods known from the literature include gradient techniques and evolutionary algorithms. The main idea of gradient methods is to calculate the gradient of the objective function at the actual point and then to step towards better values according to this value. Evolutionary algorithms imitate a simplified abstract model of evolution observed in nature. Memetic algorithms traditionally combine evolutionary and gradient techniques to exploit the advantages of both methods. Our current research aims to discover the properties, especially the efficiency (i.e. the speed of convergence) of particular evolutionary and memetic algorithms. For this purpose the techniques are compared on several numerical optimization benchmark functions and on machine learning problems. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_11