Studia Informatica

Volume: 2(6)
Year: 2005
Publishing: Publishing House of University of Podlasie
Scientific Editor: Andrzej Wisniewski
ISSN: 1731-2264


Cyran K.,
Combining Rough Sets and Neural Network Approaches in Pattern Recognition
pp. 7-20
Abstract: The paper focuses on problems which arise when two different types of AI methods are combined in one design. The first type is rule based, rough set methodology operating is highly discretized attribute space. The discretization is a consequence of the granular nature of knowledge representation in the theory of rough sets. The second type is neural network working in continuous space. Problems of combining these different types of knowledge processing are illustrated in a system used for recognition of diffraction patterns. The feature extraction is performed with the use of holographic ring wedge detector, generating the continuous feature space. No doubt, this is a feature space natural for application of the neural network. However, the criterion of optimization of the feature extractor uses rough set based knowledge representation. This latter, requires the discretization of conditional attributes generating the feature space. The novel enhanced method of optimization of holographic ring wedge detector is proposed, as a result of modification of indiscernibility relation in the theory of rough sets. Key words: Pattern recognition, neural networks, rough sets, hybrid methods, evolutionary optimization, holographic ring-wedge detectors
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Jednoralski M., Kacprzak T.,
Use of Modified Adaptive Heuristic Critic Algorithm for Novel Scheduling Mechanism in Packet-Switched Networks
pp. 21-34
Abstract: In this paper a novel scheduling algorithm of packet selection in a switch node for transmission in a network channel, based on Reinforcement Learning and modified Adaptive Heuristic Critic is introduced. A comparison of two well known scheduling algorithms: Earliest Deadline First and Round Robin shows that these algorithms perform well in some cases, but they cannot adapt their behavior to traffic changes. Simulation studies show that novel scheduling algorithm outperforms Round Robin and Earliest Deadline First by adapting to changing of network conditions. Key words: Reinforcement Learning, telecommunication networks, packets scheduling
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Kaziemierczak J.,
Automatic Programming System with Access in the Natural Language
pp. 35-47
Abstract: In this paper, acquisition of knowledge from user’s programs written in Pascal to the knowledge base of the computer is introduced. It is shown that system with such a kind of knowledge can be used as the automatic programming system. First, representation of knowledge acquired by the computer from different programs is characterized. Then searching for pieces of knowledge in the knowledge base needed for synthesis of a program specified in user requirement is described. Finally, the construction of a new program from the found pieces of knowledge is shown. Key words: Artificial intelligence, automatic programming, knowledge representation
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Pietras K., Rudnicki M.,
GPU-based Multi-Layer Perceptron as Efficient Method for Approximation Complex Light Models in Per-Vertex Lighting
pp. 53-63
Abstract: This paper describes a display method of the sky color on GeForce FX hardware. Lighting model used here is taken from “Display of the Earth taking into account atmospheric scattering” by Tomoyuki Nishita, however this model is not the only suitable one in the proposed method.
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Trajer J.,
Artificial Neural Networks in Carrot Utilization Assessment
pp. 65-68
Abstract: Carrot is a vegetable of great importance to our country. Poland is a major carrot producer in Europe. Therefore, carrot turnover, and especially quality control and its utilization, are of great importance. So far, there has been only one division of carrot into three quality categories, accepted within the European Union. The method of assessment is time-consuming and subjective. There is no method, however, which would be quick in realization and objective. Below, we proposed a quantitative carrot assessment method in the form of quality indicator and studied interdependency between carrot quality and measurable carrot colour discriminant. The indicator allows taking into consideration factors, which are decisive as regards carrot utilization.
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