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  • Articles  (8)
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  • cluster analysis  (8)
  • Springer  (8)
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  • Articles  (8)
  • Other Sources
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  • Springer  (8)
  • Institute of Physics
  • Oxford University Press
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  • 2020-2022
  • 1995-1999
  • 1985-1989
  • 1980-1984  (5)
  • 1970-1974  (3)
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  • Mathematics  (8)
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  • 1
    Electronic Resource
    Electronic Resource
    A Bayesian algorithm for global optimization (1984)
    Springer
    Annals of operations research 1 (1984), S. 111-128 
    Details
    ISSN: 1572-9338
    Keywords: Global optimization ; Bayesian nonparametric inference ; random distributions ; cluster analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract A crucial step in global optimization algorithms based on random sampling in the search domain is decision about the achievement of a prescribed accuracy. In order to overcome the difficulties related to such a decision, the Bayesian Nonparametric Approach has been introduced. The aim of this paper is to show the effectiveness of the approach when an ad hoc clustering technique is used for obtaining promising starting points for a local search algorithm. Several test problems are considered.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01876142
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  • 2
    Electronic Resource
    Electronic Resource
    Numerical classification applied to certain Jamaican eocene nummulitids (1971)
    Springer
    Mathematical geology 3 (1971), S. 297-311 
    Details
    ISSN: 1573-8868
    Keywords: classification ; cluster analysis ; discriminant analysis ; numerical taxonomy ; paleontology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Eighty-eight specimens of Eocene nummulitids from the Yellow Limestone Formation of northwestern Jamaica are classified according to quantitative measurements of morphologic parameters that are generally considered to be taxonomically useful. The specimens are grouped into homogeneous classes by the computer screening of differently oriented data projections. By this method, the use of similarity coefficients and the question of a priori weighting of characters, for which numerical taxonomy has been heavily criticized, are both avoided. The stability of the classes thus obtained is validated by discriminant analysis. These techniques provide an objective view of phenetic differences among specimens and show how the measured characters produce those differences. Tightness of coiling and total number of whorls, prove to be the most useful features in discriminating between groups but seem to have taxonomic value only at the specific and not at the generic level. This suggests that the generaOperculinoides andNummulites are synonymous.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02045797
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  • 3
    Electronic Resource
    Electronic Resource
    A new cluster algorithm for orientation data (1984)
    Springer
    Mathematical geology 16 (1984), S. 139-153 
    Details
    ISSN: 1573-8868
    Keywords: cluster analysis ; numerical taxonomy ; natural classification ; multimodality ; density estimation ; orientation data ; fabric diagrams
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract An algorithm to classify data points on the sphere in distinct cluster groups is defined. The characteristics of the cluster groups and the rule for assigning data to the groups are related to a continuous differentiable density estimation. The modes of the estimated density are assumed to be representative of the groups; data points are then assigned to the mode reached by the steepest ascent. The major advantage of this procedure is its sensitivity in detecting cluster groups independently of their geometry and configuration. As a consequence, the procedure is capable of handling orientation data that may be arranged in girdles.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01032213
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  • 4
    Electronic Resource
    Electronic Resource
    An example of cluster analysis applied to a large geologic data set: Aerial radiometric data from Copper Mountain, Wyoming (1984)
    Springer
    Mathematical geology 16 (1984), S. 479-498 
    Details
    ISSN: 1573-8868
    Keywords: aerial radiometrics ; cluster analysis ; k-means analysis ; principal components analysis ; Copper Mountain ; Wyoming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract One objective of the aerial radiometric surveys flown as part of the U.S. Department of Energy's National Uranium Resource Evaluation (NURE) program was to ascertain the spatial distribution of near-surface radioelement abundances on a regional scale. Some method for identifying groups of observations with similar γ-ray spectral signatures and radioelement concentration values was therefore required. It is shown in this paper that cluster analysis can identify such groups with or without a priori knowledge of the geology of an area. An approach that combines principal components analysis with convergentk-means cluster analysis is used to classify 6991 observations (each observation comprising three radiometric variables) from the Precambrian rocks of the Copper Mountain, Wyoming area. This method is compared with a convergentk-means analysis that utilizes available geologic knowledge. Both methods identify four clusters. Three of the clusters represent background values for the Precambrian rocks of the area, and the fourth represents outliers (anomalously high214Bi). A segmentation of the data corresponding to “geologic reality” as interpreted by other methods has been achieved by perceptive quantitative analysis of aerial radiometric data. The techniques employed are composites of classical clustering methods designed to handle the special problems presented by large data sets.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01886328
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  • 5
    Electronic Resource
    Electronic Resource
    Numeric examination of multivariate soil samples (1971)
    Springer
    Mathematical geology 3 (1971), S. 1-14 
    Details
    ISSN: 1573-8868
    Keywords: classification ; cluster analysis ; principal components analysis ; numerical taxonomy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Numerical methods for the examination of multivariate soil samples are presented in geometric terms. Techniques of coordinate representation by principal components, by nonmetric scaling, and by a new method are discussed, as are techniques for agglomerative hierarchic cluster analysis. These are illustrated by two sets of previously published data.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02047429
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  • 6
    Electronic Resource
    Electronic Resource
    Quantitative discrimination between magmatic units of the singhbhum granite (1971)
    Springer
    Mathematical geology 3 (1971), S. 123-133 
    Details
    ISSN: 1573-8868
    Keywords: cluster analysis ; distance functions ; mineralogy ; petrology ; structure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The weight-percent values of four mineralogic variables (quartz, K feldspar, color index, and muscovite) for 10 sets of granitic rocks (20–50 samples in each set) from magmatic units of the Singhbhum granite were used for (1) computation of the Mahalanobis' generalized distance functions (D 2) between all pairs of the 10 sets, (2) testing significance of the difference between the multivariate means, and (3) computation of the linear discriminant functions between all possible pairs of the sets. The 10 data sets are for six magmatic units which belong to three successive but closely related phases of emplacement. The multivariate means for all sets are significantly different except for those between two of the sets of phase I. Cluster analysis on the basis of theD 2 values enables the 10 sets to be placed into four distinct groups. Group A includes two subgroups, one of which consists of two sets representing typical members of phase I; the other subgroup includes two sets which are typical of phase II. Group B includes two sets which are typical of phase III. The other four sets do not group with the typical representatives of the three phases, probably because of certain special conditions of their emplacement. A separate series ofD 2 computation from the same data, but excluding the color index, was unsuccessful in making the four aberrant sets group with the typical members of the respective phases. Efficient LDF's could be determined for discrimination between most pairs of the 10 sets of granite rocks.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02045956
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  • 7
    Electronic Resource
    Electronic Resource
    Application of fuzzy clustering and fuzzy classification to evaluate the provenance of glacial till (1984)
    Springer
    Mathematical geology 16 (1984), S. 283-301 
    Details
    ISSN: 1573-8868
    Keywords: Bayesian classifiers ; classification ; cluster analysis ; cluster validity ; fuzzyc means ; fuzzyc varieties ; fuzzy covariances ; geochemical prospecting ; glacial till ; kriging
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract To evaluate the provenance of glacial till, the trace element content of magnetite was used. Magnetite was present in all known rock types and all till samples in the area investigated. By using fuzzy-set theory it was possible to group samples of magnetite taken from bedrock into relatively homogeneous and geologically meaningful groups and also, by fuzzy classification, to relate the till samples to the rocks in such a way that the relative contribution of each rock type to the till is estimated. Each rock and till sample is assigned a membership value between 0 and 1 for each rock type. The membership values, for a certain rock type in the till, are then interpolated by kriging onto maps. Magnetites from skarns associated with sulfide ores especially are rather distinct, and so a map of such membership values for till unveils all known ore deposits some 1–5 km “downstream”in the general direction of the ice flow. Other anomalies show up which cannot be related to hitherto known ores or mineralizations.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01032692
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  • 8
    Electronic Resource
    Electronic Resource
    A method for stratigraphic correlation of several boreholes (1984)
    Springer
    Mathematical geology 16 (1984), S. 393-406 
    Details
    ISSN: 1573-8868
    Keywords: geophysical logs ; multivariate statistics ; cluster analysis ; linear programming ; dynamic programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The borehole slotting method previously proposed by Gordon and Reyment for two boreholes may be extended to three or more boreholes, but soon becomes computationally intractable. We propose another method based on the mixture model of cluster analysis, the computational labor of which increases linearly with the number of boreholes. This method produces profiles of the unknown strata to which the individual boreholes are easily matched by the two-borehole slotting method.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01029888
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