In this paper, extended Runge-Kutta fourth order method for directly solving the fuzzy logistic problem is presented. The extended Runge-Kutta method has lower number of function evaluations, compared with the classical Runge-Kutta method. The numerical robustness of the method in parameter estimation is enhanced via error minimization in predicting growth rate and carrying capacity. The results of fuzzy logistic model with the estimated parameters have been compared with population growth data in Malaysia, which indicate that this method is more accurate that the data population. Numerical example is given to illustrate the efficiency of the proposed model. It is concluded that robust parameter estimation technique is efficient in modelling population growth.
In numerical methods, boundary element method has been widely used to solve
acoustic problems. However, it suffers from certain drawbacks in terms of computational
efficiency. This prevents the boundary element method from being applied to large-scale
problems. This paper presents proposal of a new multiscale technique, coupled with
boundary element method to speed up numerical calculations. Numerical example is
given to illustrate the efficiency of the proposed method. The solution of the proposed
method has been validated with conventional boundary element method and the proposed
method is indeed faster in computation.