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Property Land Processes using Radial Basis Neural Network Methods
Nor Syazwani Binti Shaharin.
Supervisor: Assoc. Prof. Dr. Muhammad Safiih Bin Lola
Bachelor of Science (Computational Mathematics)
School Of Informatics and Applied Mathematics
Heavy rainfall and critical infrastructures are the reason why landslide can happen.
However, the danger of landslides can be mitigated if the hazard zone is predictable and
mapped before any arming activities are carried out. So to assist in reducing the incidence
of landslides, this study was conducted to build a model using the RBFNN method. Test
the model that has been built using the RBFNN, whether the method is effective in
calculating errors in data. Radial Basis neural network (RBFNN) is the mapping
mechanism of a multivariate information space to another. It can help finding the right
value of correlation between the factor of soil collapse and soil displacement. Therefore,
the results of this study show that the RBFNN method is the best way to overcome the
problem of landslide because this method is able to estimate vulnerable areas to
landslides using space databases for certain areas.
967 | UMT UNDERGRADUATE RESEARCH DAY 2018