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    Random Field Modeling of CPT Data 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2000:;Volume ( 126 ):;issue: 012
    Author(s): Mark B. Jaksa; Gordon A. Fenton
    Publisher: American Society of Civil Engineers
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    Inaccuracies Associated with Estimating Random Measurement Errors 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;1997:;Volume ( 123 ):;issue: 005
    Author(s): Mark B. Jaksa; Peter I. Brooker; William S. Kaggwa
    Publisher: American Society of Civil Engineers
    Abstract: This paper examines a commonly used procedure, proposed by Baecher, for separating the random measurement error associated with a particular test from the inherent spatial variability of the geological material. By comparing ...
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    Closure to “Inaccuracies Associated with Estimating Random Measurement Errors” by Mark B. Jaksa, Peter I. Brooker, and William S. Kaggwa 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;1999:;Volume ( 125 ):;issue: 001
    Author(s): Mark B. Jaksa; Peter I. Brooker; William S. Kaggwa
    Publisher: American Society of Civil Engineers
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    Closure to “Predicting Settlement of Shallow Foundations Using Neural Networks” by Mohamed A. Shahin, Holger R. Maier, and Mark B. Jaksa 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2003:;Volume ( 129 ):;issue: 012
    Author(s): Mohamed A. Shahin; Holger R. Maier; Mark B. Jaksa
    Publisher: American Society of Civil Engineers
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    Predicting Settlement of Shallow Foundations using Neural Networks 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2002:;Volume ( 128 ):;issue: 009
    Author(s): Mohamed A. Shahin; Holger R. Maier; Mark B. Jaksa
    Publisher: American Society of Civil Engineers
    Abstract: Over the years, many methods have been developed to predict the settlement of shallow foundations on cohesionless soils. However, methods for making such predictions with the required degree of accuracy and consistency ...
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    Data Division for Developing Neural Networks Applied to Geotechnical Engineering 

    Source: Journal of Computing in Civil Engineering:;2004:;Volume ( 018 ):;issue: 002
    Author(s): Mohamed A. Shahin; Holger R. Maier; Mark B. Jaksa
    Publisher: American Society of Civil Engineers
    Abstract: In recent years, artificial neural networks (ANNs) have been applied to many geotechnical engineering problems with some degree of success. In the majority of these applications, data division is carried out on an arbitrary ...
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    Inaccuracies Associated with Estimating Random Measurement Errors 

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;1999:;Volume ( 125 ):;issue: 001
    Author(s): Gregory B. Baecher; Mark B. Jaksa; Peter I. Brooker; William S. Kaggwa
    Publisher: American Society of Civil Engineers
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