Outlier phenomenon in data interpretation for one waves scattering problem

• Autorzy: Emets V. F. , Rogowski J.
• Języki publikacji: EN

Abstrakty

EN

An outlier is an observation (or measurement) that is different with respect to the other values contained in a given data set. Outliers can occur due to several causes. The measurement can be incorrectly observed, recorded or processed or otherwise is correctly measured but represents a rare event. In this paper it is shown that observed data can contain values that differ from expected ones and can be interpreted as an outlier, but in fact are caused by a specific physical phenomenon.

Słowa kluczowe

EN

outlier phenomenon; acoustic wave scattering

PL

zjawisko wyjątku; rozproszenie fali akustycznej

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2017
• Tom: Vol. 25, nr 2
• Strony: 43--51
• Opis fizyczny: Bibliogr. 12 poz., wykr.

Twórcy

autor

Emets V. F.

• Institute of Information Technology, Lodz University of Technology, Wolczanska Str. 215, 90-924, Lodz, Poland

autor

Rogowski J.

• Institute of Information Technology, Lodz University of Technology, Wolczanska Str. 215, 90-924, Lodz, Poland

Bibliografia

• [1] Aggarwal, C. C., Outlier Analysis, 2nd ed., IBM T. J. Watson Research Center, Yorktown Heights, New York, 2016.
• [2] Angiulli, F. and Pizzuti, C., Fast outlier detection in high dimensional spaces, In: Principles of Data Mining and Knowledge Discovery, Lecture Notes in Artificial Intelligence, vol. 2431, edited by T. Elomaa, H. Mannila, and H. Toivonen, Springer, Berlin, Heidelberg, 2002.
• [3] Cateni, S., Colla, V., and Vannucci, M., Outlier detection methods for industrial applications, In: Advances in robotics, automation and control, edited by J. Arámburo and A. R. Trevińo, I-Tech, Vienna, 2008.
• [4] Loureiro, A., Torgo, L., and Soares, C., Outlier Detection Using Clustering Methods: a Data Cleaning Application, In: Proceedings of the data mining for business workshop, 2004.
• [5] Pahuja, D. and Yadav, R., Outlier Detection for Different Applications: Review, International Journal of Engineering Research and Technology, Vol. 2, No. 3, 2013.
• [6] Yu, D., Sheikholeslami, G., and Zhang, A., FindOut: Finding outliers in very large datasets, Knowledge and Information Systems, Vol. 4, No. 4, 2002.
• [7] Duraj, A. and Szczepaniak, P., Information Outliers and Their Detection, In: Information Studies and the Quest for Transdisciplinarity, edited by M. Burgin and W. Hofkirchner, World Scientific Publishing Company, 2017.
• [8] Chomątek, L. and Duraj, A., Multiobjective Genetic Algorithm for Outliers Detection, In: IEEE International Conference on INnovations in Intelligent SysTems and Applications INISTA 2017, Gdynia, Poland, 3-5 July, 2017.
• [9] Smoliński, M., Resolving Classical Concurrency Problems Using Adaptive Conflictless Scheduling, In: IEEE International Conference on Innovations in Intelligent SysTems and Applications INISTA 2017, Gdynia, Poland, 3-5 July, 2017.
• [10] Emets, V. F. and Rogowski, J., Mathematical-numerical modeling of ultrasonic scattering data from a closed obstacles and inverse analysis, Academic Publishing House EXIT, Warsaw, 2013.
• [11] Emets, V. F. and Rogowski, J., Scattering from a strip with PEC and partially PMC boundaries, In: 18th International Conference on Computational Problems of Electrical Engineering, 2017.
• [12] Emets, V. F. and Rogowski, J., Diffraction by a Strip with Different Boundary Conditions on Its Surfaces, In: 16th International Conference on Computational Problems of Electrical Engineering, 2015.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).