Application FCM in modelling DIR for Selangor using negative binomial GAM

Mohamad, Nazeera and Che Him, Norziha and Rusiman, Mohd Saifullah and Sufahani, Suliadi and Muhammad Jamil, Siti Afiqah (2018) Application FCM in modelling DIR for Selangor using negative binomial GAM. International Journal of Engineering & Technology, 7 (4.3). pp. 1-4. ISSN 2227-524X

Full text not available from this repository. (Request a copy)

Abstract

This study attempts to obtain the best fitted model among two clusters which describe the relationship between dengue incidence rate (DIR) and relevant covariates such as climatic and non-climatic variables. The significant variables include amount of rainfall and number of rainy days with lag 0 until 3 months, number of locality and population density. Fuzzy C-Means clustering (FCM) was applied in clustering DIR data based on the value of membership function. The boundary of membership function has been set as 0.5. There are two clusters identified in this study with Cluster 1 consist of 569 data and Cluster 2 consist of 43 data. Then, this study developed models to predict future dengue incidences in Selangor by using negative binomial Generalised Additive Model (GAM). The result shows that the model able to be one of tools for future development in controlling and reducing the number of dengue cases particularly in Selangor, Malaysia as well as other states.

Item Type: Article
Uncontrolled Keywords: AIC; DIR; Fuzzy C-Means; membership function; negative binomial GAM
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Q Science > QA Mathematics > QA299.6-433 Analysis
T Technology > TA Engineering (General). Civil engineering (General) > TA329-348 Engineering mathematics. Engineering analysis
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistics
Depositing User: UiTM Student Praktikal
Date Deposited: 09 Jan 2022 07:51
Last Modified: 09 Jan 2022 07:51
URI: http://eprints.uthm.edu.my/id/eprint/5465

Actions (login required)

View Item View Item