Prediction of Cantilever Retaining Wall Stability using Optimal Kernel Function of Support Vector Machine

Prediction of Cantilever Retaining Wall Stability using Optimal Kernel Function of Support Vector Machine

The Support Vector Machine is one of the artificial intelligence techniques that can be applied to forecast the stability of cantilever retaining walls. The selection of the right Kernel function is very important so that the Support Vector Machine model can make good predictions. However, there are...

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Bibliographic Details
Main Authors: Alias, R. (Author), Ibrahim, A. (Author), Matlan, S.J (Author)
Format: Article
Language:English
Published: Science and Information Organization 2021
Series:International Journal of Advanced Computer Science and Applications
Subjects:
Artificial intelligence techniques
Cantilever retaining wall
Cantilever retaining walls
Cross validation
Error values
Forecasting
Functions
kernel function
Kernel function
Mean square error
Means square errors
Nanocantilevers
Optimal kernels
prediction
Radial basis function networks
Retaining walls
Squared correlation coefficients
stability
Stability
support vector machine
Support vector machine models
Support vector machines
Support vectors machine
Vectors
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