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008 121116s2013 xxu| s |||| 0|eng d
020 _a9781441902368
_9978-1-4419-0236-8
024 7 _a10.1007/978-1-4419-0236-8
_2doi
050 4 _aQA402.5-402.6
072 7 _aPBU
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519.6
_223
100 1 _aDzemyda, Gintautas.
_eauthor.
245 1 0 _aMultidimensional Data Visualization
_h[electronic resource] :
_bMethods and Applications /
_cby Gintautas Dzemyda, Olga Kurasova, Julius Žilinskas.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXII, 252 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Optimization and Its Applications,
_x1931-6828 ;
_v75
505 0 _aPreface -- 1. Multidimensional Data and the Concept of Visualization -- 2. Strategies for Multidimensional Data Visualization -- 3. Optimization-Based Visualization -- 4. Combining Multidimensional Scaling with Artificial Neural Networks -- 5. Applications of Visualizations -- A. Test Data Sets -- References -- Index.
520 _aThe goal of this book is to present a variety of methods used  in multidimensional data visualization. The emphasis is placed on new research results and trends in this field, including optimization, artificial neural networks, combinations of algorithms, parallel computing, different proximity measures, nonlinear manifold learning,  and more. Many of the applications presented allow us to discover the obvious advantages of visual data mining—it is much easier for a decision maker to detect or extract useful information from graphical representation of data than from raw numbers. The fundamental idea of visualization is to provide data in some visual form that lets humans  understand them, gain insight into the data, draw conclusions, and directly influence the process of decision making. Visual data mining is a field where human participation is integrated in the data analysis process; it covers data visualization and graphical presentation of information. Multidimensional Data Visualization is intended for scientists and researchers in any field of study where complex and multidimensional data must be visually represented. It may also serve as a useful research supplement for PhD students in operations research, computer science, various fields of engineering,  as well as natural and social sciences.
650 0 _aMathematics.
650 0 _aArtificial intelligence.
650 0 _aComputer simulation.
650 0 _aVisualization.
650 0 _aMathematical optimization.
650 1 4 _aMathematics.
650 2 4 _aOptimization.
650 2 4 _aSimulation and Modeling.
650 2 4 _aVisualization.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aKurasova, Olga.
_eauthor.
700 1 _aŽilinskas, Julius.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441902351
830 0 _aSpringer Optimization and Its Applications,
_x1931-6828 ;
_v75
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4419-0236-8
912 _aZDB-2-SMA
942 _2Dewey Decimal Classification
_ceBooks
999 _c43392
_d43392