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    Behavior of Cantilever Retaining Walls 

    Source: Journal of Geotechnical Engineering:;1993:;Volume ( 119 ):;issue: 011
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
    Abstract: Current methods for retaining‐wall analysis are based on the classical theoretical formulations of Rankine or Coulomb, with the assumption that sufficient lateral yield will occur to mobilize fully active conditions behind ...
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    Closure to “Modeling Soil Correlations Using Neural Networks” by Anthony T. C. Goh 

    Source: Journal of Computing in Civil Engineering:;1997:;Volume ( 011 ):;issue: 001
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
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    Modeling Soil Correlations Using Neural Networks 

    Source: Journal of Computing in Civil Engineering:;1995:;Volume ( 009 ):;issue: 004
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
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    Closure to “Behavior of Cantilever Retaining Wall” by Anthony T. C. Goh 

    Source: Journal of Geotechnical Engineering:;1995:;Volume ( 121 ):;issue: 002
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
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    Seismic Liquefaction Potential Assessed by Neural Networks 

    Source: Journal of Geotechnical Engineering:;1994:;Volume ( 120 ):;issue: 009
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
    Abstract: The feasibility of using neural networks to model the complex relationship between the seismic and soil parameters, and the liquefaction potential has been investigated. Neural‐networks are information‐processing systems ...
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    Neural-Network Modeling of CPT Seismic Liquefaction Data 

    Source: Journal of Geotechnical Engineering:;1996:;Volume ( 122 ):;issue: 001
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
    Abstract: The use of the cone-penetration-test (CPT) resistance data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because of the popularity of this in situ test method for the ...
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    Pile Driving Records Reanalyzed Using Neural Networks 

    Source: Journal of Geotechnical Engineering:;1996:;Volume ( 122 ):;issue: 006
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
    Abstract: Pile driving formulas are commonly used to estimate the load capacity of driven piles. The formulas assume that there is a correlation between the pile set and the ultimate load capacity of the pile. The important factors ...
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    Closure to “Seismic Liquefaction Potential Assessed by Neural Networks” by Anthony T. C. Goh 

    Source: Journal of Geotechnical Engineering:;1996:;Volume ( 122 ):;issue: 004
    Author(s): Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
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    Municipal Solid‐Waste Incinerator Fly Ash for Geotechnical Applications 

    Source: Journal of Geotechnical Engineering:;1993:;Volume ( 119 ):;issue: 005
    Author(s): Anthony T. C. Goh; Joo‐Hwa Tay
    Publisher: American Society of Civil Engineers
    Abstract: Many highly urbanized cities are faced with the problem of disposal of municipal solid waste because of the scarcity of land available for landfilling. One possible solution is the incineration of the municipal solid waste. ...
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    Engineering Properties of Incinerator Residue 

    Source: Journal of Environmental Engineering:;1991:;Volume ( 117 ):;issue: 002
    Author(s): Joo‐Hwa Tay; Anthony T. C. Goh
    Publisher: American Society of Civil Engineers
    Abstract: For highly urbanized cities where there is a scarcity of available land for landfilling, incineration may be a better method of solid‐waste disposal. After incineration about 20% by weight of ash and other residues are ...
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