01023531

Component

https://doi.org/10.3141/1936-22

http://scholar.google.com...Garg&publication_year=2005

The incomprehensible loss of lives and extensive damages to transportation facilities caused by earthquakes emphasize the need for robust and reliable methods for evaluating the liquefaction potential of sites. Traditional methods for evaluating liquefaction potential are based on correlating data from the standard penetration test (blow count, N), cone penetration test (cone resistance, q sub c), or the shear wave velocity (V sub s) with the cyclic stress ratio. These methods are unable to incorporate the complex influence of various soil and in situ state parameters. This problem encouraged the development of numerous nontraditional methods such as artificial neural networks that try to learn and account for the influence of various soil and in situ state properties. The possibility of using neural networks based on adaptive resonance theory (ART) for the prediction of liquefaction potential was explored. These networks have been shown to be far more efficient and reliable than the commonly used backpropagation artificial neural network and other multilayer perceptrons. Two Fuzzy ARTMAP (FAM) models were developed and tested with q sub c and V sub s data obtained from past case histories. The q sub c- and V sub s-based FAM models gave overall successful prediction rates of 98% and 97%, respectively. The promising results obtained by the FAM models exemplify the potential of nontraditional computing methods for evaluating liquefaction potential.

01023507

English

pp 192-200

2005

Transportation Research Record: Journal of the Transportation Research Board

0309094100

Print

Figures (3) ; References (21) ; Tables (7)

Liquefaction; Mathematical prediction; Neural networks

Adaptive resonance theory

Data and Information Technology; Geotechnology; Highways; I42: Soil Mechanics

TRIS, TRB

Apr 26 2006 1:14PM

• Accelerated Strength Improvement of Silty Sand with Nontraditional Additives
• Approach to Evaluating Damage from Thermal Bridge Displacements
• Comparison of the Bidirectional Load Test with the Top-Down Load Test
• Cyclic Plate Load Testing of Geosynthetic-Reinforced Unbound Aggregate Roads
• Design of Ribbed Concrete Approach Slab Based on Interaction with the Embankment
• Development and Application of a Rut Prediction Model for Flexible Pavement
• Development of Methodology to Include Structural Contribution of Alternative Working Platforms in Pavement Structure
• Development of U.S. Army Corps of Engineers Engineering Guidance for the Barge Impact Design of Navigation Structures
• Early-Age Strength Assessment of Cement-Treated Base Material
• Ettringite Formation in Lime-Treated Soils: Establishing Thermodynamic Foundations for Engineering Practice
• Field Installation and Pullout Test of Embedded Suction Anchors
• Full-Scale Experimental Measurement of Barge Impact Loads on Bridge Piers
• Geogrid-Reinforced Pile-Supported Railway Embankments : A Three-Dimensional Numerical Analysis
• Improvement of the Geotechnical Axial Design Methodology for Colorado’s Drilled Shafts Socketed in Weak Rocks
• Improving Effectiveness and Reliability in Geotechnical Investigations with a Personal Digital Assistant
• Modeling Water Flow Patterns in Flexible Pavements
• Performance of an Induced Trench Installation
• Permeability of Base Material for Maine Roads
• Pore Pressure Measurement in Blast-Induced Liquefaction Experiments
• Practical Approach to Criteria for the Use of Lime–Fly Ash Stabilization in Base Courses
• Real-Time Compaction Monitoring in Cohesive Soils from Machine Response
• Reliability Analysis of Cracking and Faulting Prediction in the New Mechanistic–Empirical Pavement Design Procedure
• Stabilization Techniques for Unpaved Roads
• Structural Contribution of Geosynthetic-Reinforced Working Platforms in Flexible Pavement
• Use of Microcracking to Reduce Shrinkage Cracking in Cement-Treated Bases