Wyniki wyszukiwania - BazTech

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Reliability and Efficiency of Differential Evolution Based Method of Determination of Jiles-Atherton Model Parameters for X30CR13 Corrosion Resisting Martensitic Steel

Biedrzycki R., Jackiewicz D., Szewczyk R.

Journal of Automation Mobile Robotics and Intelligent Systems

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2014

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Vol. 8, No. 4

63--68

EN

Paper presents new possibilities of Jiles-Atherton model of magnetic hysteresis parameters determination. The main problem connected with this model is the fact that its parameters have to be determined during the optimization process. However, due to the local minima on the target function, the gradient optimization methods are not effective, whereas evolutionary strategies, such as (μ+λ) strategy, are very time consuming. Results of calculation presented in the paper indicate that differential strategies create possibility of reliable and fast determination of Jiles-Atherton model parameters. Paper also presents guidelines for practical determination of model’s parameters, which is very important from practical point of view.

2

KIS: An automated attribute induction method for classification of DNA sequences

Biedrzycki R., Arabas J.

International Journal of Applied Mathematics and Computer Science

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2012

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Vol. 22, no. 3

711-721

EN

This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites. We also show how to use the algorithm to find a human readable model of the IRE (Iron-Responsive Element) and to find IRE sequences. The method, although universal, yields results which are of quality comparable to those obtained by reference methods. In contrast to reference methods, this approach uses models that operate on sequence patterns, which facilitates interpretation of the results by humans.

3

DNA sequence analysis

Biedrzycki R.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2007

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z. 160

35-42

EN

This paper presents a brief survey of computational approaches to the DNA sequence analysis. The basic biological background is presented. The various types of algorithms for pattern construction and gene finding are presented with special attention paid to the application of global optimization methods.

4

Evolutionary and greedy exploration of the space of decision trees

Biedrzycki R., Arabas J.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2006

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z. 156

61-68

EN

This paper addresses the issue of the decision trees induction. We define the space of all possible trees and try to find good trees by searching that space. We compare performance of an evolutionary algorithm and standard, problem-specific algorithms (ID3, C4.5).