Publication: Analisis taburan hujan di sitiawan menggunakan rangkaian neural
| dc.contributor.author | Abu Kasim, Yazid Bin | |
| dc.date.accessioned | 2024-08-08T03:02:23Z | |
| dc.date.available | 2024-08-08T03:02:23Z | |
| dc.date.issued | 2007-03-01 | |
| dc.description.abstract | This paper is about artificial intelligence (AI) applications to analyze rainfall in Sitiawan. Beside that, statistical analysis also have been use to analyze rainfall. The AI techniques include artificial neural networks, expert system, fuzzy system and multivariate regression while statistical analysis can be done using SPSS, Stata or SAS. For this project, multilayer perceptron has been chosen among other methodology in neural network. The data consists of 360 data which include 30 years of data from January 1951 to December 1980. All 360 data were divided onto 2 sets of data: a set of 200 samples for training phase and the remaining 160 samples are used to test for the validity and applicability of the artificial intelligence neural network approach. Neural network can detect rainfall or not through the learning process. Matlab 7 is used to design multilayer perceptron. A learning algorithm used in this project to train the multilayer perceptron is Bayesian regularization algorithm. Training process will be done first before testing process. Testing process is used to determine how accurate neural network system in analyze rainfall. From training and testing, the result of back propagation algorithm gives a high percentage of accuracy. The percentage is 100%. The results proved that the multilayer perceptron network has high capability to analyze rainfall in Sitiawan. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/20133 | |
| dc.language.iso | other | |
| dc.title | Analisis taburan hujan di sitiawan menggunakan rangkaian neural | |
| dc.type | Resource Types::text::report | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |