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  • 1
    Electronic Resource
    Electronic Resource
    Evaluation of precursory seismic quiescence in sixteen subduction zones using single-link cluster analysis (1990)
    Springer
    Pure and applied geophysics 134 (1990), S. 57-78 
    Details
    ISSN: 1420-9136
    Keywords: Earthquake precursors ; clustering ; quiescence ; earthquake statistics ; seismicity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract This paper describes a new method, single-link cluster analysis (SLC), to evaluate percursory quiescence for shallow earthquakes in sixteen subduction zones, using data from the ISC catalog. To define quiescent regions, we divided the catalog into time intervals with a durationT, overlapping byT/2. We considered all earthquakes having magnitudes larger than some magnitudeM min, lying within a specified distance of a great circle which is approximately coincident with the trench near a subduction zone. Within each time interval we connected or ‘linked’ all earthquakes lying within some cutoff distanced of one another. We then projected all these links onto the great circle, and defined a region to be quiescent if it was not covered by the projection of any links. For this study,T was two years,M min wasm b =4.9, and we variedd from 100 to 400 km. We defined an earthquake as ‘following quiescence’ if it occurred within two years following, and within 75 km of a quiescent zone as defined above. The primary conclusion of this study was that earthquakes with surface wave magnitudes 7.2 and greater were about 5–15% more likely to follow quiescence than were the smaller background earthquakes withm b 〉-4.9. A chi-squared analysis shows that this result is significant at the 99% level. In contrast, earthquakes with surface wave magnitude of 6.7 to 7.1 were no more likely to follow quiescence than were background earthquakes. Of sixteen individual regions, Central America, Japan, and Peru-Chile were the only regions where large earthquakes were more likely to occur following quiescence than were background earthquakes. For a cutoff link length of 300 km, only in Central America was the difference between large earthquakes and background earthquakes significant at the 95% level of significance. For a cutoff link length of 250 km, the significance level exceeded 95% only in Japan. The SLC method is an objective, quantitative method for evaluating large data catalogs, or for monitoring quiescence in regions where quiescence is conjectured to precede large earthquakes.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00878080
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  • 2
    Electronic Resource
    Electronic Resource
    A Theory for Memory-Based Learning (1994)
    Springer
    Machine learning 17 (1994), S. 143-167 
    Details
    ISSN: 0885-6125
    Keywords: Memory-based learning ; PAC learning ; clustering ; approximation ; linear programming ; relaxation ; covering ; hashing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract A memory-based learning system is an extended memory management system that decomposes the input space either statically or dynamically into subregions for the purpose of storing and retrieving functional information. The main generalization techniques employed by memory-based learning systems are the nearest-neighbor search, space decomposition techniques, and clustering. Research on memory-based learning is still in its early stage. In particular, there are very few rigorous theoretical results regarding memory requirement, sample size, expected performance, and computational complexity. In this paper, we propose a model for memory-based learning and use it to analyze several methods— ∈-covering, hashing, clustering, tree-structured clustering, and receptive-fields—for learning smooth functions. The sample size and system complexity are derived for each method. Our model is built upon the generalized PAC learning model of Haussler (Haussler, 1989) and is closely related to the method of vector quantization in data compression. Our main result is that we can build memory-based learning systems using new clustering algorithms (Lin & Vitter, 1992a) to PAC-learn in polynomial time using only polynomial storage in typical situations.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1022667616941
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  • 3
    Electronic Resource
    Electronic Resource
    A theory for memory-based learning (1994)
    Springer
    Machine learning 17 (1994), S. 143-167 
    Details
    ISSN: 0885-6125
    Keywords: Memory-based learning ; PAC learning ; clustering ; approximation ; linear programming ; relaxation ; covering ; hashing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract A memory-based learning system is an extended memory management system that decomposes the input space either statically or dynamically into subregions for the purpose of storing and retrieving functional information. The main generalization techniques employed by memory-based learning systems are the nearest-neighbor search, space decomposition techniques, and clustering. Research on memory-based learning is still in its early stage. In particular, there are very few rigorous theoretical results regarding memory requirement, sample size, expected performance, and computational complexity. In this paper, we propose a model for memory-based learning and use it to analyze several methods— ε-covering, hashing, clustering, tree-structured clustering, and receptive-fields—for learning smooth functions. The sample size and system complexity are derived for each method. Our model is built upon the generalized PAC learning model of Haussler (Haussler, 1989) and is closely related to the method of vector quantization in data compression. Our main result is that we can build memory-based learning systems using new clustering algorithms (Lin & Vitter, 1992a) to PAC-learn in polynomial time using only polynomial storage in typical situations.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00993469
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  • 4
    Electronic Resource
    Electronic Resource
    Genotype by environment effects and selection for drought tolerance in tropical maize. I. Two mode pattern analysis of yield (1997)
    Springer
    Euphytica 95 (1997), S. 01-09 
    Details
    ISSN: 1573-5060
    Keywords: water stress ; breeding ; adaptation ; G × E ; clustering ; ordination ; Zea mays ; corn ; maize
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Abstract Ten trials evaluated the performance of several late tropical maize populations (La Posta Sequía, Pool 26 Sequía and Tuxpeño Sequía) selected for tolerance to drought during flowering and grain filling and also for yield potential. Families (S1 or full-sib) had been selected recurrently for six to eight years on an index of traits. Pattern (clustering and ordination) analysis was used to analyse the relative performance of entries that included cycles of selection for drought tolerance in the populations and non-drought tolerant checks. Mean environment (E) yields ranged from 1.0 to 10.4 t ha-1. Analysis of variance showed that 97.9% of the total sums of squares was accounted for by E, and that, of the remaining sums of squares the G × E (genotype by environment interaction) was almost 3 times that of the contribution of G alone. Cluster analysis separated the checks, the earlier maturing drought tolerant entries and the later maturing drought tolerant entries. This was verified by principal component (PC) analysis of the G × E matrix. Grouping of the environments (i.e. based on entry performance), resulted in the separation of different types of droughts, and of medium and high yielding well-watered environments. The patterns of discrimination observed indicated that the yield gains under drought would have been unlikely to occur if selection had been done only in well-watered environments. Within each population, selection improved broad adaptation (higher mean yield) to both drought and well-watered environments and cycles of selection ‘jumped’ from non-drought-tolerant to drought-tolerant groups as their specific adaptation to drought environments increased.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002918008679
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  • 5
    Electronic Resource
    Electronic Resource
    Genotype by environment effects and selection for drought tolerance in tropical maize. II. Three-mode pattern analysis (1997)
    Springer
    Euphytica 95 (1997), S. 11-20 
    Details
    ISSN: 1573-5060
    Keywords: water stress ; breeding ; ordination ; clustering ; three-way analysis ; Zea mays ; corn
    Source: Springer Online Journal Archives 1860-2000
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Abstract A selection program in three tropical maize populations aimed to improve tolerance of mid-season to late season drought environments while maintaining grain yield (GY) potential. The selection process employed other attributes that included maintaining a constant anthesis date (AD) and, under drought, shortening the anthesis-silking interval (ASI) and increasing ear number per plant (EPP). Three-mode (genotypes × environments × attributes) pattern analysis, which consists of clustering and ordination, should be able to collectively interpret these changes from ten evaluation trials. Mixture maximum likelihood clustering identified four groups that indicated the populations' performance had changed with selection. Groups containing the advanced cycles of selection were higher yielding in most environments and had lower ASI and higher EPP, particularly in drought environments. Check entries with no selection for drought tolerance remained grouped with the initial cycles of selection. A 3 × 2 × 3 (genotypes by environments by attributes) principal component model explained 70% of the variation. For the first environmental component, ASI was shown to be highly negatively correlated with both GY and EPP while anthesis date (AD) was virtually uncorrelated with other traits. The second environmental component (explaining 10% of the variation) contrasted droughted and well-watered environments and showed that EPP and GY were better indicators of this contrast (in terms of changes in population performance) than were AD or ASI. Three-mode analysis demonstrated that improvements with selection occurred in both droughted and well-watered environments and clearly summarised the overall success of the breeding program.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1002922527795
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