COMPLETE PPIMG

(MLR) and principal component regression (PCR) method for prediction of chlorophyll-a
water quality and to test the effectiveness of the model developed in by using
hybridization ANN with MLR and PCR. Issues highlighted here are to develop the best and
most accurate method to predict the chlorophyll-a in water quality and to determine the
comparison between hybridization of ANN with MLR and PCR methods. The results of this
comparison methods show that only one method is chosen to develop the new model of
ANN. It can be concluded, once the model developed from the method chosen, the ANN
model able to gain the new data set.
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
312 | UMT UNDERGRADUATE RESEARCH DAY