Neural Networks Approach for Predicting Slope Failure Areas Based on the Onsite Slope Survey Parameters at a Specified Mountain Road
Journal Title: International Journal of Engineering Innovations and Research - Year 2018, Vol 7, Issue 3
Abstract
This study proposed a new method of using a neural network model for predicting slope failure areas by training different slope parameters obtained from 49 onsite slope failure surveys in a specified mountain road section. The developed model has three input parameters including slope height, slope horizontal distance, and rainfall factor. With three neurons in the hidden layer, a relatively better performance for predicting a slope failure area can be obtained in the output layer, based on the evaluation indices of a correlation coefficient and a mean square error. For all the data sets in the neural network calculation process, the square value of a correlation coefficient between the prediction result and the survey data reached up to 0.8020, which may imply that the developed model has an acceptable reliability. The current study has presented a simple way for dealing with this type of slope failure problem, and the obtained results may provide useful information for the relevant engineering agency to improve road safety in the mountain road region investigated.
Authors and Affiliations
Tienfuan Kerh, et al.
Keywords
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