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Title: STABILITY OF CUT SLOPES AGAINST SHALLOW FAILURE: EVALUATION BY NEURAL NETWORK MODEL
Accession Number: 00960141
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: The discrimination model for road cut slope stability was used to assess 216 cut slope locations on the Chuo Expressway. This model ranks the failure probability of slopes by the rainfall threshold (cumulative precipitation that causes the slope to fail) to identify slopes highly prone to collapse. Because of the complexity (nonlinearity) of the relationship between the factors relating to the cut slope failure and the precipitation that triggers a failure, it has been difficult to correctly evaluate the likelihood of failure for cut slopes. The developed model has overcome that difficulty by involving the neural network as the discrimination technique. The input data included the different factors (topography, soil properties and geology, surface layer status, change in state) in the stability investigation table prepared at the time of road slope inspection, with additional information such as catchment topography. The cut slope data were prepared, referring to a variety of information encompassing the failure history for 30 years after the commencement of service, the rainfall record at the time of failure, the maximum rainfall amount ever recorded, and the data on the status of slope protection around the time of failure. As shown by the discrimination results, the model accuracy (ratio of correct answers to number of slopes evaluated) was as high as approximately 80%, which allowed accurate determination of the amounts of rainfall inducing the failure of different slopes.
Supplemental Notes: This paper appears in Transportation Research Record No. 1821, Geology and Properties of Earth Materials 2003.
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Matsuyama, HOGATA, KAmano, KPagination: p. 104-114
Publication Date: 2003
Serial: ISBN: 0309085535
Features: Figures
(10)
; References
(3)
; Tables
(5)
TRT Terms: Geographic Terms: Subject Areas: Data and Information Technology; Geotechnology; Highways; I42: Soil Mechanics
Files: TRIS, TRB, ATRI
Created Date: Jul 22 2003 12:00AM
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