Hamizah Mohd Safuan

Impacts of Biotic Resource Enrichment on a Predator–Prey Population

The environmental carrying capacity is usually assumed to be fixed quantity in the classical predator–prey population growth models. However, this assumption is not realistic as the environment generally varies with time. In a bid for greater realism, functional forms of carrying capacities have been widely applied to describe varying environments. Modelling carrying capacity as a state variable serves as another approach to capture the dynamical behavior between population and its environment. The proposed modified predator–prey model is based on the ratio-dependent models that have been utilized in the study of food chains. Using a simple non-linear system, the proposed model can be linked to an intra-guild predation model in which predator and prey share the same resource. Distinct from other models, we formulate the carrying capacity proportional to a biotic resource and both predator and prey species can directly alter the amount of resource available by interacting with it. Bifurcation and numerical analyses are presented to illustrate the system’s dynamical behavior. Taking the enrichment parameter of the resource as the bifurcation parameter, a Hopf bifurcation is found for some parameter ranges, which generate solutions that posses limit cycle behavior.

On travelling wave solutions of the diffusive Leslie-Gower model

We investigate the diffusive Leslie-Gower predator-prey model. Travelling wave solutions were found and a minimum wave speed relationship was derived. Linear stability analysis was performed in addition to full numerical simulation of the model. All travelling waves were found to be stable.

Hydromagnetic flow and heat transfer adjacent to an unsteady stretching vertical sheet with prescribed surface heat flux

The unsteady hydromagnetic flow adjacent to a stretching vertical sheet is studied. The unsteadiness in the flow and temperature fields is caused by the time dependence of the stretching velocity and the surface heat flux. The governing partial differential equations are reduced to nonlinear ordinary differential equations, before being solved numerically. Comparison with previously published results as well as the exact solution for the steady-state case of the present problem is made, and the results are found to be in good agreement. Effects of the unsteadiness parameter, magnetic parameter, and Prandtl number on the flow and heat transfer are fully examined.

Neural network versus classical time series forecasting models

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

Food chain model with competition interaction in an environment of a biotic resource

Population interactions generally describe the interactions of populations that compete for available food or other resources. We study a food chain model with competition interaction in an environment characterized by a biotic resource. The model consists of a population of two species that share the same resource. Stability, bifurcation and numerical analyses are presented to illustrate the system’s dynamical behaviour. The transitions from persistence to extinction of a species are identified and give rise to certain threshold conditions. Numerical analyses demonstrate that the inter-specific competition parameters determined the survival of one species over the other.