The application of fuzzy logistic equations in population growth with parameter estimation via minimization
This paper presents a numerical solution for the first order fuzzy logistic equations by extended Runge-Kutta fourth order method with estimated parameters. The parameters are estimated by minimization technique using conjugate gradient approach. Then, the fuzzy logistic model with the estimated par...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Published: |
Penerbit UTM Press
2017
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/80944/ http://dx.doi.org/10.11113/mjfas.v13n2.564 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |
| Summary: | This paper presents a numerical solution for the first order fuzzy logistic equations by extended Runge-Kutta fourth order method with estimated parameters. The parameters are estimated by minimization technique using conjugate gradient approach. Then, the fuzzy logistic model with the estimated parameters is used to fit the population growth in Malaysia. Numerical example is given to show the efficiency of the proposed model. |
|---|