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Warianty tytułu
Języki publikacji
Abstrakty
Methods of multi-parameter data visualization through the transformation of multidimensional space into two-dimensional one allow to present multidimensional data on computer screen, thus making it possible to conduct a qualitative analysis of this data in the most natural way for human – by a sense of sight. In the paper a comparison was made to show the efficiency of selected seven methods of multidimensional visualization and further, to analyze data describing various coal type samples. Each of the methods was verified by checking how precisely a coal type can be classified when a given method is applied. For this purpose, a special criterion was designed to allow an evaluation of the results obtained by means of each of these methods. Detailed information included presentation of methods, elaborated algorithms, accepted parameters for best results as well the results. The framework for the comparison of the analyzed multi-parameter visualization methods includes: observational tunnels method multidimensional scaling MDS, principal component analysis PCA, relevance maps, autoassociative neural networks, Kohonen maps and parallel coordinates method.
Rocznik
Tom
Strony
769--784
Opis fizyczny
Bibliogr. 41 poz., rys., tab.
Twórcy
autor
- AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Applied Computer Science, al. Mickiewicza 30, 30-059 Krakow, Poland
autor
- AGH University of Science and Technology, Faculty of Mining and Geoengineering, Department of Environmental Engineering and Mineral Processing, al. Mickiewicza 30, 30-059 Krakow
Bibliografia
- AHMED H.A.M., DRZYMALA J. (2005), Two-dimensional fractal linearization of distribution curves, Physicochemical Problems of Mineral Processing, 39, 129-139.
- ALDRICH C. (1998), Visualization of transformed multivariate data sets with autoassociative neural networks, Pattern Recognition Letters, 19(8), 749-764.
- ASIMOV D. (1985), The Grand Tour: A Tool for Viewing Multidimensional Data, SIAM Journal of Scientific and Statistical Computing, 6, 128-143.
- ASSA J., COHEN-OR D., MILO T. (1999), RMAP: a system for visualizing data in multidimensional relevance space, Visual Computer, 15(5), 217-234.
- BONDAREV A.E., GALAKTIONOV V.A., CHECHETKIN V.M. (2011), Analysis of the development concepts and methods of visual data representation in computational physics, Computational Mathematics and Mathematical Physics, 51(4), 624-636.
- BROZEK M., SUROWIAK A. (2010), Argument of Separation at Upgrading in the Jig, Archives of Mining Sciences, 55(1), 21-40.
- BROZEK M., SUROWIAK A. (2007), Effect of Particle Shape on Jig Separation Efficiency, Physicochemical Problems of Mineral Processing, 41, 397-413.
- BROZEK M., SUROWIAK A. (2005), The Dependence of Distribution of Settling Velocity of Spherical Particles on the Distribution of Particle Sizes and Densities, Physicochemical Problems of Mineral Processing, 39, 199-210.
- CLEVELAND W.S., MCGILL R. (1984), The many faces of a scatterplot, Journal of the American Statistical Association, 79, 807-822.
- DRZYMALA J. (2009), Basics of minerallurgy, Oficyna Wydawnicza Politechniki Wroclawskiej, Wroclaw. [in Polish]
- DRZYMALA J. (2007), Mineral processing: foundations of theory and practice of minerallurgy, Oficyna Wydawnicza Politechniki Wroclawskiej, Wroclaw.
- GAWENDA T., SARAMAK D., TUMIDAJSKI T. (2005), Regression models of rock materials crushing in jaw crushers, Scientific Issues of Civil Engineering and Environmental Engineering Faculty of Koszalin University of Science and Technology, series: Environmental Engineering, 22, 659-670. [in Polish]
- EINBECK J., EVERS L., BAILER-JONES C. (2007), Representing Complex Data Using Localized Principal Components with Application to Astronomical Data, in GORBAN A., KEGL B., WUNSCH D., ZINOVYEV A. (eds.), Principal Manifolds for Data Visualisation and Dimension Reduction, LNCSE 58, Springer, Berlin – Heidelberg – New York, 180-204.
- HOTELLING H. (1933), Analysis of a complex of statistical variables into principal components, Journal of Educational Psychology, 24, 417-441 and 498-520.
- INSELBERG A. (2009), Parallel Coordinates: VISUAL Multidimensional Geometry and its Applications, Springer.
- JAIN A.K., MAO J. (1992), Artificial neural network for non-linear projection of multivariate data, in: Proc. IEEE Internat. Joint Conf. On Neural Networks, Baltimore, MD, 3, 335-340.
- JAMROZ D. (2014a), Application of Multidimensional Data Visualization in Creation of Pattern Recognition Systems, in GRUCA A., CZACHORSKI T., KOZIELSKI S. (eds.),, Man-Machine, Interactions 3, AISC, Switzerland, Springer International Publishing, 242, 443-450.
- JAMROZ D. (2014b), Application of multidimensional scaling to classification of various types of coal, Archives of Mining Sciences, 59(2), 413-425.
- JAMROZ D. (2014c), Application of multi-parameter data visualization by means of autoassociative neural networks to evaluate classification possibilities of various coal types, Physicochemical Problems of Mineral Processing, 50(2), 719-734.
- JAMROZ D. (2009), Multidimensional labyrinth - multidimensional virtual reality, in CYRAN K., KOZIELSKI S., PETERS J., STANCZYK U., WAKULICZ-DEJA A. (eds.),, Man-Machine, Interactions, AISC, Heidelberg, Springer-Verlag, 59, 445–450.
- JAMROZ D., NIEDOBA T. (2015), Application of multidimensional data visualization by means of self-organizing Kohonen maps to evaluate classification possibilities of various coal types, Archives of Mining Sciences, 60(1), 39-50.
- JAMROZ D., NIEDOBA T. (2014), Application of Observational Tunnels Method to Select Set of Features Sufficient to Identify a Type of Coal, Physicochemical Problems of Mineral Processing, 50(1), 185-202.
- JAMROZ D. (2001), Visualization of objects in multidimensional spaces, Doctoral Thesis, AGH, Krakow. [in Polish]
- JOLLIFFE I.T. (2002), Principal Component Analysis, Springer Series in Statistics, 2nd ed., Springer, NY.
- KOHONEN T. (1989), Self Organization and Associative Memory, Springer-Verlag.
- KRUSKAL J. B. (1964), Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis, Psychometrika, 29, 1–27.
- LYMAN G. J. (1993), Application of Line-Length Related Interpolation Methods to Problems in Coal Preparation – III: Two dimensional Washability Data Interpolation, Coal Preparation, 13, 179-195.
- NIEDOBA T., JAMROZ D. (2013), Visualization of multidimensional data in purpose of qualitative classification of various types of coal, Archives of Mining Sciences, 58(4), 1317-1333.
- NIEDOBA T. (2013a), Multidimensional characteristics of random variables in description of grained materials and their separation processes, Wydawnictwo Instytutu Gospodarki Surowcami Mineralnymi i Energia PAN, Krakow. [in Polish].
- NIEDOBA T. (2009), Multidimensional distributions of grained materials characteristics by means of non-parametric approximation of marginal statistical density function, AGH Journal of Mining and Geoengineering, 33(4), 235-244. [in Polish].
- NIEDOBA T. (2014), Multi-parameter data visualization by means of principal component analysis (PCA), in qualitative evaluation of various coal types, Physicochemical Problems of Mineral Processing, 50(2), 575-589.
- NIEDOBA T. (2015), Application of relevance maps in multidimensional classification of coal types, Archives of Mining Sciences, vol. 60(1), 93-106.
- NIEDOBA T. (2013b), Statistical analysis of the relationship between particle size and particle density of raw coal, Physicochemical Problems of Mineral Processing, 49(1), 175-188.
- NIEDOBA T., SUROWIAK A. (2012), Type of coal and multidimensional description of its composition with density and ash contents taken into consideration, in Proceedings of the XXVI International Mineral Processing Congress, 1, 3844-3854.
- NIEDOBA T. (2011), Three-dimensional distribution of grained materials characteristics, in Proceedings of the XIV Balkan Mineral Processing Congress, Tuzla, Bosnia and Herzegovina, 1, 57-59.
- OLEJNIK T., SUROWIAK A., GAWENDA T., NIEDOBA T., TUMIDAJSKI T. (2010), Multidimensional coal characteristics as basis for evaluation and adjustment of its beneficiation technology, AGH Journal of Mining and Geoengineering, 34(4/1), 207-216. [in Polish]
- SARAMAK D. (2013), Mathematical models of particle size distribution in simulation analysis of High-pressure grinding rolls operation, Physicochemical Problems of Mineral Processing, 49(1), 495–512.
- SARAMAK D. (2011), Technological Issues Of High-Pressure Grinding Rolls Operation In Ore Comminution Processes, Archives of Mining Sciences, 56(3), 517-526.
- SNOPKOWSKI R., NAPIERAJ A. (2012), Method Of The Production Cycle Duration Time Modeling Within Hard Coal Longwall Faces, Archives of Mining Sciences, 57(1), 121-138.
- TUMIDAJSKI T., SARAMAK D. (2009), Methods and models of mathematical statistics in mineral processing, Wydawnictwo AGH, Krakow. [in Polish]
- TUMIDAJSKI T. (1997), Stochastic analysis of grained materials properties and their separation processes, Wydawnictwo AGH, Krakow. [in Polish]
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e57ce769-568d-47a9-a591-88fee096a611