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2 Journal of Theoretical and Applied Computer Science

2 2014

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Improved Particle Swarm Optimization method for investment strategies parameters computing

Bera A., Sychel D., Sacharski B .

Journal of Theoretical and Applied Computer Science

2014

Vol. 8, nr 4

45--55

The paper studies the problem of computing the parameters for investment strategies. Proposed is an innovative modification of Particle Swarm Optimization algorithm for discrete and continuous data. The article shows how discrete and continuous version of the algorithm can be combined in order to achieve the best results. Moreover, the presented algorithm is expanded by a multi-swarm mechanism which allows to achieve better results in a fixed time. The proposed algorithm was tested on a simple investment strategy, based on one of the well known indicators Rate of Change (further referred as ROC) that uses a mixture of discrete and continuous parameters. All the tests were performed on a data gathered from one of the most important of currency pairs — EURUSD.

Automated blurred image region classification

Bera A., Sacharski B ., Sychel D.

Journal of Theoretical and Applied Computer Science

2014

Vol. 8, nr 2

37--47

In this paper authors present a simple method for recognizing blurred regions in the image. Proposed algorithm is based on 81 simple features — moments of histogram of image subbands, that were obtained during image decomposition, and ratio derived from gray level co-occurrence matrix (GLCM) are used. The method is compared with a different method, that is based on approaches found in literature. To increase the efficiency of algorithms, authors combined three solutions (edge-detection, gray level co-occurrence matrix and fast image sharpness). The aim of the research was to verify whether it is possible to use simpler methods of feature extraction to achieve similar, or even better, results.