Optimization of sample size and epidemic model parameters by using the differential evolution and optimization algorithms | |
| Author | Uruthiran, Peranantham |
| Call Number | AIT RSPR no.CS-12-10 |
| Subject(s) | Epidemiology Mathematical models Public health surveillance Computer algorithms |
| Note | A Research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no. CS-12-10 |
| Abstract | This research work focuses on epidemic surveillance by using SIR model. The objective of this research is to optimize the parameters of an epidemic model and its sample size. As any surveillance requires a proper sample size, the calculated sample size should be sufficient for the surveillance; otherwise it will not be useful for the disease analysis and decision making process. In this research, differential evolution algorithm and optimization algorithm are employed to optimize the sample size and the parameters of SIR model respectively. Hence, the “optim ” functions are used to find optimum value of susceptible, infected and transmission rate at the initial state |
| Year | 2012 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no. CS-12-10 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Duboz, Raphael; |
| Examination Committee(s) | Phan Minh Dung;Poompat Saengudomlert; |
| Scholarship Donor(s) | Asian Development Bank, Technical Development Education Training Project Sri Lanka / Asian Institute of Technology Fellowship; |
| Degree | Research report (M. Sc.) - Asian Institute of Technology, 2012 |