Browsing by Author "Islam, Saeed"

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    Intelligent computing for electromagnetohydrodynamic bioconvection flow of micropolar nanofluid with thermal radiation and stratification: Levenberg–Marquardt backpropagation algorithm
    (AIP Advances, 2024-03) Khan, Zeeshan; Alfwzan, Wafa F.; Ali, Aatif; Nisreen, Innab; Zuhra, Samina; Islam, Saeed; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    The Levenberg–Marquardt (LM) backpropagation optimization algorithm, an artificial neural network algorithm, is used in this study to perform integrated numerical computing to evaluate the electromagnetohydrodynamic bioconvection flow of micropolar nanofluid with thermal radiation and stratification. The model is then reduced to a collection of boundary value problems, which are solved with the help of a numerical technique and the proposed scheme, i.e., the LM algorithm, which is an iterative approach to determine the minimum of a nonlinear function defined as the sum of squares. As a blend of the steepest descent and the Gauss–Newton method, it has become a typical approach for nonlinear least-squares problems. Furthermore, the stability and consistency of the algorithm are ensured. For validation purposes, the results are also compared with those of previous research and the MATLAB bvp4c solver. Neural networking is also utilized for velocity, temperature, and concentration profile mapping from input to output. These findings demonstrate the accuracy of forecasts and optimizations produced by artificial neural networks. The performance of the bvp4c solver, which is used to reduce the mean square error, is used to generalize a dataset. The artificial neural network-based LM backpropagation optimization algorithm operates using data based on the ratio of testing (13%), validation (17%), and training (70%). This stochastic computing work presents an activation log-sigmoid function based LM backpropagation optimization algorithm, in which tens of neurons and hidden and output layers are used for solving the learning language model. The overlapping of the results and the small computed absolute errors, which range from 10−3 to 10−10 and from 106 to 108 for each model class, indicate the accuracy of the artificial neural network-based LM backpropagation optimization algorithm. Furthermore, each model case’s regression performance is evaluated as if it were an ideal model. In addition, function fitness and histogram are used to validate the dependability of the algorithm. Numerical approaches and artificial neural networks are an excellent combination for fluid dynamics, and this could lead to new advancements in many domains. The findings of this research could contribute to the optimization of fluid systems, resulting in increased efficiency and production across various technical domains.
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    Mathematical modeling for the transmission potential of Zika virus with optimal control strategies
    (Springer , 2022-01) Ali, Aatif; Iqbal, Quaid; Asamoah, Joshua Kiddy K.; Islam, Saeed; 0000-0002-7066-246X
    In this paper, we formulate a new Zika virus model in light of both mosquito and human transmission along with the human awareness in the host population. Initially, we assumed that the virus is transmitted to humans through a mosquito bite and then transmits to his or her sexual partner. Further, we investigated the mathematical results and stability analysis and proved that the model is asymptotically stable both locally and globally. We applied the Castillo-Chavez approach for establishing global stability. Similarly, we presented the existence of endemic equilibrium and demonstrate that the model is locally and globally asymptotically stable using a suitable Lyapunov function at endemic state, upon backward bifurcation analysis we proposed that no bifurcation exists for our model. The sensitivity analysis is carried out and verified that the probability per biting of the susceptible mosquito with the infected human is the most sensitive parameter. Furthermore, we developed a Zika control model and incorporated three controls. These controls are prevention through bed nets and mosquito repellents, treatment of Zika patients, and the spray of insecticides on mosquitoes. The graphical results of the model with control and without control are obtained through a numerical scheme. The infection caused by the Zika virus would be more efficiently eliminated using the new idea of human awareness and bilinear incidence presented in this paper.