Final Year Projects (FYPs)

Now showing 1 - 3 of 3

Dynamics of a Vector-Host SIR-SI Model in Dengue Transmission
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Rayan Zahid; CIIT/SP21-BSM-001/LHR; Dr. Syed Tahir Raza Rizvi; LHR TP 9877
Dengue fever is a major health problem, especially in tropical and subtropical areas, affect- ing around 50 countries. The disease is mainly spread by Aedes mosquitoes, with Aedes aegypti being the most important carrier. Urbanization, climate change, and population movement make it spread more easily. Dengue symptoms can range from mild fever to se- vere hemorrhagic fever, which can be fatal. To control the disease, effective strategies are needed, and epidemiological models are crucial for understanding disease spread, testing interventions, and predicting outbreaks. In this project, we will create a model that describes the relationship between humans and mosquitoes using a susceptible-infected-recovered (SIR) model for people and a susceptible- infected (SI) model for mosquitoes. The goal is to understand how these two groups in- teract and use this information to improve control measures. We will calculate the basic reproduction number (Ro) using the Next Generation Matrix method to determine whether the disease will spread (Ro > 1) or fade out (Ro < 1). We will also use stability analysis with the Lyapunov function to check these results. Furthermore, we will run simulations in MATLAB to test the model and explore the effects of control measures like mosquito population control, vaccination, and quarantine. By doing sensitivity analysis, we will identify the most important factors affecting disease spread and help prioritize the best in- terventions. The project aims to provide useful insights into how dengue spreads and guide effective ways to control it.
Study of fractional nonlinear Schr¨odinger equation for soliton solutions
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Azrar-Ul-Hassan (CIIT/FA20-BSM-036/LHR), M. Raheel (CIIT/FA20-BSM-045/LHR); Dr. Syed Tahir Raza Rizvi; LHR TP 9905
The fact that nonlinear partial differential equations (NLPDEs) are used in practically ev- ery academic domain including biology, chemistry, physics, mechanics, ﬁber optics, at- mospheric science, and electronics research makes them signiﬁcant. One special kind of NLPDE is the nonlinear Schr¨odinger equation (NLSE), research in the ﬁelds of engineer- ing, biology, and physics has uses for the NLSE. A major subject of nonlinear model re- search during the past 20 years has been the soliton, an essential description in the NLSE analysis. Particularly, the development of optical solitons has given nonlinear optics a the- oretical foundation. In the framework of the time-fractional cubic-quintic nonlinear Schr¨odinger equation (TFCQ- NLSE), the analysis of soliton solutions is the main emphasis of this work. Wide-ranging applications of this adaptive model can be found in many complicated real phenomena, such as ﬁber optic communication, nonlinear optics, optical signal processing, laser-tissue interaction in medical science, and many others. The intensity of the cubic and quintic non- linear components determines the observed nonlinear effects, which include self-focusing, self-phase modulation, and wave-mixing. This model’s investigation employs a robust analytical approach. Our sub-ode approach, will be multitude of potential solitons and furnishes details on the interactions of laser pulses, was employed to explore this model. This inquiry yields numerous illustrated soliton solutions. Among these solutions are those that are hyperbolic, rational, singular, bright, Jacobian elliptic solutions (JES), Weierstrass elliptic solutions (WES) and periodic solutions (PS)
Application of Bilinear Neural Network Method to Sawada-Kotera Model
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Syeda Maryam Zahra; CIIT/SP21-BSM-013/LHR; Dr. Syed Tahir Raza Rizvi; LHR TP 9882
In this work, we use the bilinear neural network method (BNNM) for solving the (2+1)- dimensional bidirectional Sawada-Kotera (bSK) equation. This model is the extension of the famous Korteweg-de Vries (KdV) equation which represents the shallow water waves on surfaces. Firstly, we use generalized Hirota bilinear approach (gHBA) and then by us- ing BNNM, we obtain exact analytical solution. BNNM is an important step toward the integration of neural networks with classic methodologies for nonlinear partial differential equations (NLPDEs), presenting both the solution in exact form and offering powerful vi- sualization of complex phenomena. This may be a method applied to a wide range of ﬁelds such as plasma, optics, acoustics, ﬂuid dynamics, and so on. BNNM models the neural network with a tensor formula and derives the exact solutions by symbolic computation. This neural network consists of layers, with their contribution in ﬁnding the solutions using activation functions and weight matrices. This method generates new test functions and in this thesis, the test functions consist of ”3-2-1” and ”3-3-1” neural network models. Here ”3-2-1” means 3 neurons in input layer, 3 neurons in ﬁrst hidden layer and a single neuron in second hidden layer. Lump, lump with one kink, rogue wave, and breather lump soliton and periodic solution for the governing model will be obtained by BNNM with the men- tioned layer. Sev

Final Year Projects (FYPs) - Undergraduates

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