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  • Articles  (6)
  • cluster analysis  (3)
  • linear model  (2)
  • Aegean, back arc structure  (1)
  • Springer  (6)
  • American Meteorological Society
  • American Physical Society (APS)
  • Cambridge University Press
  • De Gruyter
  • Ovid Technologies
  • Oxford University Press
  • Seismological Society of America
  • Springer Nature
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  • 2000-2004
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  • Articles  (6)
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  • Springer  (6)
  • American Meteorological Society
  • American Physical Society (APS)
  • Cambridge University Press
  • De Gruyter
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  • 2000-2004
  • 1980-1984  (6)
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Pure and applied geophysics 120 (1982), S. 820-839 
    ISSN: 1420-9136
    Keywords: Attenuation ; Aegean, back arc structure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract A detailed study of P and S waves from earthquakes located along the Hellenic arc and recorded by the Greek seismological network, shows an abnormal distribution of the seismic waves in the central Aegean Sea. The data indicate a zone of anomalously high seismic wave attenuation in the Upper Mantle beneath the Cyclades plateau and the inner part of the volcanic arc. Several independent observations suggest the presence of magma beneath the Cyclades massif. In addition, geophysical data indicate the presence of low-density and rigidity material. Theoretical consideration of the propagation of elastic waves corroborate the observed absence of shear waves.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 14 (1982), S. 161-187 
    ISSN: 1573-8868
    Keywords: beach sand ; shape ; specific gravity ; size ; grains ; linear model ; variance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The influence of shape, size, and specific gravity of mineral grains on the variation of the content of these minerals in beach sands has been investigated for fixed conditions of sedimentation on the beaches of the Baltic Sea and Michigan Lake. The coefficient of variation was used as a measure of the variance. Linear models tested by the analysis of variance were applied and revealed that the shape of grains and the combined effect of the size and specific gravity are responsible for the main part of the variation.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 14 (1982), S. 405-417 
    ISSN: 1573-8868
    Keywords: Markov Chain ; carbonate sequences ; cluster analysis ; substitutability analysis ; entropy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract It is difficult to develop stochastic models for complex lithological sequences that are typically associated with intertidal-supratidal depositional environments. A sequence from the Upper Silurian Leopold Formation on eastern Somerset Island is used to demonstrate that a combination of cluster analysis, Markov Chain analysis, and substitutability analysis can give considerable insight into the nature of such complex successions. The high variability of this sequence was created by a combination of (a) variation in the depositional environment, (b) variation in the degree of dolomitization, (c) variation in the clastic influx, (d) random highenergy (possibly storm associated events) and (e) random breaks in the succession of depositional environments.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 14 (1982), S. 661-667 
    ISSN: 1573-8868
    Keywords: biotopes ; Bray-Curtis ; cluster analysis ; foraminifera
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Transformation of data effectively limits the distortion by outlying values on the Bray-Curtis similarity measure. It represents an effective method of using cluster analysis in distinguishing biotopes of benthic foraminifera.
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 14 (1982), S. 249-257 
    ISSN: 1573-8868
    Keywords: co-kriging ; cross-variance ; cross-variogram ; joint estimation ; estimation variance ; matrix form ; linear model ; trace
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The matrix form of the general co-kriging problem is presented. Matrix solutions are given for SRFs with covariance functions, for IRFs of order zero using variograms and for universal co-kriging. General methods for obtaining cross-covariance or cross-variogram models are given. The relationship of the general co-kriging problem to the problem of one under sampled variable is presented.
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 14 (1982), S. 259-270 
    ISSN: 1573-8868
    Keywords: cluster analysis ; EXTENDED QMODEL ; filtering ; fuzzyc-means ; fuzzy sets ; linear unmixing ; QMODEL ; shape analysis ; substructure analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Many data sets can be viewed as a collection of samples representing mixtures of a relatively small number of end members. When end members are present in the sample set, the algorithm QMODEL by Klovan and Miesch can efficiently determine proportionate contributions. EXTENDED QMODEL by Full, Ehrlich, and Klovan was designed to deduce the composition of realistic end members when the end members are not represented by samples. However, in the presence of high levels of random variation or outliers not belonging to the system of interest, EXTENDED QMODEL may not be reliable inasmuch as it is largely dependent on extreme values for definition of an initial mixing polyhedron. FUZZY QMODEL utilizes the fuzzy c-means algorithm of Bezdek to provide an alternative initial mixing polyhedron. This algorithm utilizes the collective property of all the data rather than outliers and so can produce suitable solutions in the presence of noisy or “messy” data points.
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