Pongsumpun, Puntani

Preferred name

Pongsumpun, Puntani

Alternative Name

Pongsumpun, P.

Main Affiliation

School of Science

puntani.po@kmitl.ac.th

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Influenza transmission model by dynamical analysis and cellular automata
(2020-09-30)
Pongsumpun, Puntani
The infection of the airways and lung called as influenza. The influenza cases occurred every year. We can find influenza cases around the world. Influenza is an acute respiratory disease. Symptoms of the disease include fever, headache, myalgia, sore throat and cough. Children who infected with influenza may be associated with gastrointestinal symptoms such as nausea, vomiting, and diarrhea. The influenza cases are found in children and adults. SEIR model (S = susceptible, E = exposed, I = infectious, R = recovered) is described for the transmission of influenza. We analyzed the model by using dynamical analysis and Cellular automata is done to see the spread of influenza. The effects of each parameters influence to the transmission of this disease are shown.
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Local Stability of Influenza Virus with Vaccination
(2020-05-15)
Pongsumpun, Puntani
Influenza virus is an infectious disease. This caused by influenza virus. The symptoms consist of high fever, runny nose, sore throat, muscle and joint pain. In this paper, we construct the mathematical model for the transmission of influenza virus.We separate the human into 2 groups such as group of persons who obtain the vaccination and group of persons who do not obtain the vaccination. Each group, we separated the persons intothe susceptible, exposed, infectious, quarantined and recovered groups. We analyzed the equilibrium point and find the local stability of them by using standard dynamical modeling method. The basic reproduction number of this mathematical model is found. We obtain the condition for the disease fee steady state and endemic disease state will be local stability. Numerical results of the model are shown.
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Local and global stability analysis of dengue disease with vaccination and optimal control
(2021-10-01)
Chamnan, Anusit
;
Pongsumpun, Puntani
;
Tang, I. Ming
;
Wongvanich, Napasool
Dengue fever is a disease that has spread all over the world, including Thailand. Dengue is caused by a virus and there are four distinct serotypes of the virus that cause dengue DENV‐1, DENV‐2, DENV‐3, and DENV‐4. The dengue viruses are transmitted by two species of the Aedes mosquitoes, the Aedes aegypti, and the Aedes albopictus. Currently, the dengue vaccine used in Thailand is chimeric yellow tetravalent dengue (CYD‐TDV). This research presents optimal control which studies the vaccination only in individuals with a documented past dengue infection (seropositive), regardless of the serotypes of infection causing the initial infection by the disease. The analysis of dengue transmission model is used to establish the local asymptotically stabilities. The property of symmetry in the Lyapunov function an import role in achieving this global asymptotically stabilities. The optimal control systems are shown in numerical solutions and conclusions. The result shows that the control resulted in a significant reduction in the number of infected humans and infected vectors.
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A modified optimal control for the mathematical model of dengue virus with vaccination
(2023-01-01)
Pongsumpun, Puntipa
;
Lamwong, Jiraporn
;
Tang, I. Ming
;
Pongsumpun, Puntani
The dengue viruses (of which there are four strains) are the causes of three illnesses of increasing severity; dengue fever (DF), dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). Recently, dengue fever has reached epidemic proportion in several countries. Strategies or preventative methods have to be developed to combat these epidemics. This can be done by development of vaccines or by preventing the transmission of the virus. The latter approach could involve the use of mosquito nets or insecticide spraying. To determine which strategy would work, we test the strategy using mathematical modeling to simulate the effects of the strategy on the dynamics of the transmission. We have chosen the Susceptible-Exposed-Infected-Recovered (SEIR) model and the Susceptible, Exposed-Infected (SEI) model to describe the human and mosquito populations, repectively. We use the Pontryagin’s maximum principle to find the optimal control conditions. A sensitivity analysis revealed that the transmission rate (ɣ<inf>ℎ</inf>, ɣ<inf>v</inf>), the birth rate of human population (µ<inf>ℎ</inf>), the constant recruitment rate of the vector population (A) and the total human population (N<inf>ℎ</inf>) are the most influential factors affecting the disease transmission. Numerical simulations show that the optimal controlled infective responses, when implemented, cause the convergence to zero to be faster than that in uncontrolled cases.
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Analysis of the Mathematical Model of Covid-19 in Thailand
(2021-08-20)
Pongsumpun, Puntani
The purpose of this research is to study the characteristics of the COVID-19 virus in Thailand. We formulate the mathematical model of COVID-19 virus. We separate the human populations into 6 groups. The infected human populations are separated into 2 classes such as infectious human population with no show symptom and infectious human population with symptoms. We study the behavior of the equilibrium points of the model. Determine the conditions for the local stability of the equilibrium points. Numerical results of mathematical models are presented. This will lead to a reduction in the mortality rate of patients in Thailand.
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Local stability analysis of mathematical model of Tuberculosis disease in Thailand
(2021-01-15)
Pongsumpun, Puntani
Tuberculosis (TB) is a contagious disease that is caused by Mycobacterium. It can be transmitted by air. When infected Tuberculosis speaks, coughs or sneezes. TB is present in the sputum droplets and rises into the air. Large aerosol particles often fall on the ground and dry out. The main symptom of tuberculosis is a chronic cough that lasts 2 weeks or more. Other symptoms may include loss of appetite, weight loss, fatigue, fever, chest pain, shortness of breath. This disease is transmitted between human. In this paper, we find the dynamical equations of this disease. We analyzed our mathematical model to find the equilibrium points of our mathematical model. Numerical solutions are analyzed to see the distribution of each group of population. The basic reproduction number of the disease is derived. The influence of each factor is analyzed.
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Fractional-order modeling of dengue dynamics: exploring reinfection mechanisms with the Atangana–Baleanu derivative
(2025-08-01)
Lamwong, Jiraporn
;
Pongsumpun, Puntani
Dengue fever poses ongoing public health challenges due to its complex reinfection dynamics and antibody-dependent enhancement (ADE). To address limitations in classical models, this study proposes a novel fractional-order model utilizing the Atangana–Baleanu–Caputo derivative to capture memory and non-local effects inherent in dengue transmission. The model explicitly incorporates reinfection mechanisms and stages of infection, offering a more accurate depiction of disease progression. The existence and uniqueness of solutions are established using fixed-point theory, and the global stability of equilibria is analyzed via Lyapunov methods. Model fitting with real-world data from Thailand in 2023 confirms predictive accuracy, while sensitivity analysis identifies the biting and mosquito mortality rates as critical parameters influencing the basic reproduction number. This framework enhances the realism of epidemic models and provides actionable insights for designing targeted public health interventions in dengue-endemic regions.
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Dynamical model of rabies disease in human and dog
(2022-04-28)
Pongsumpun, Puntani
Rabies causes inflammation of the brain in humans and other mammals. This is a viral disease. Every year, there are about 59,000 people worldwide die from rabies. About 99 percent of them have been bitten by dogs. This study, we formulated the dynamical model consider the transmission of rabies disease. The most important animals which transmit this disease are dogs, cats and possibly other animals. We consider the transmission of rabies virus between human and dog populations. The dynamical model is separated into human and dog populations. The standard dynamical analysis is used to analyze this model. The local and global stabilities are analyzed.
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Fractional-order Modeling and Optimal Control of Dengue-Malaria Co-infection with Local and Advanced Treatment Strategies
(2026-01-01)
Pongsumpun, Puntipa
;
Ud Din, Rahim
;
Ullah, Atta
;
Pongsumpun, Puntani
Abstract: This study presents a novel fractional-order co-infection model describing the joint transmission dynamics of dengue and malaria using the generalized fractional derivative. The total human population is divided into eight epidemiological compartments that account for single infections, co-infection, treatment stages, and recovery. The proposed framework incorporates memory effects and nonlocal behavior, offering a more realistic representation of disease progression compared to classical integer-order models. Local and advanced treatment strategies are introduced based on infection severity, allowing targeted intervention for both mild and co-infected cases. The fundamental mathematical properties of the model, including positivity, boundedness, existence, and uniqueness of solutions, are rigorously established. The basic reproduction number is derived, and both local and global stability of the disease-free equilibrium are analyzed using suitable Lyapunov functions. A statistical sensitivity analysis is performed to identify key parameters influencing disease transmission. Furthermore, optimal control strategies are formulated to minimize co-infection prevalence while reducing treatment and implementation costs. Numerical simulations validate the theoretical findings and demonstrate that fractional-order dynamics provide deeper insights into long-term disease behavior. The results offer valuable guidance for policymakers in designing effective and cost-efficient strategies to control dengue and malaria co-infection. Graphic Abstract: (Figure presented.) The
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Levenberg-Marquardt neural network-based intelligent computation for the non-Newtonian polymer during forward roll coating
(2023-11-01)
Ali, Fateh
;
Hou, Yanren
;
Feng, Xinlong
;
Zahid, M.
;
Ali, Muhammad Usman
Scientists and researchers widely recognize the effectiveness of artificial intelligence (AI)-based machine learning and intelligent computing solvers, demonstrating qualities such as resilience, robustness, stability, and rapid convergence. One particularly significant and rapidly growing field within AI is artificial neural networks. This research uses a supervised neural network model based on Levenberg-Marquardt backpropagation (LMB-SNNs) to examine the Sisko fluid model for the forward roll coating process (SFM-FRCP). A suitable transformation is applied to the partial differential equations based SFM-FRCP mathematical model, resulting in a set of nonlinear ordinary differential equations. The perturbation method has been used to find the analytical solutions for the velocity profile, pressure gradient, and pressure profile. A dataset for varying the pertinent parameters is generated, and the LMB-SNNs technique has been used to estimate the velocity profile, pressure gradient, and pressure profile behavior during FRCP for numerous scenarios. The numerical solution for SFM-FRCP in different scenarios, such as the validation, training, and testing procedures of LMB-SNNs, is carried out. Moreover, the state transition index, fitness outline, mean square error, histogram error, and regression presentation also endorse the strength and reliability of the solver LMB-SNNs for SFM-FRCP. The comparative analyses and performance studies through outputs of regression drawings, absolute error, and error histograms validate the effectiveness of the suggested solver LMB-SNNs. The method's precision is verified by the closest numerical outputs of both built and dataset values with similar levels 10 − 11 - 10 − 14 . Furthermore, it has been observed that as the non-Newtonian parameter increases, the fluid velocity decreases. The research work carried out in this paper is original and fills a gap in the existing research by showing the rheological properties of the Sisko fluid model and the implementation of the LMB-SNNs during the FRCP.

Pongsumpun, Puntani

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