This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations ove...This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations over four distinct time intervals.The model incorporates three key fractional derivatives:the Caputo-Fabrizio fractional derivative with a non-singular kernel,the Caputo proportional constant fractional derivative with a singular kernel,and the Atangana-Baleanu fractional derivative with a non-singular kernel.We analyze the stability of the core model and apply various numerical methods to approximate the proposed crossover model.To achieve this,the approximation of Caputo proportional constant fractional derivative with Grünwald-Letnikov nonstandard finite difference method is used for the deterministic model with a singular kernel,while the Toufik-Atangana method is employed for models involving a non-singular Mittag-Leffler kernel.Additionally,the integral Caputo-Fabrizio approximation and a two-step Lagrange polynomial are utilized to approximate the model with a non-singular exponential decay kernel.For the stochastic component,the Milstein method is implemented to approximate the stochastic differential equations.The stability and effectiveness of the proposed model and methodologies are validated through numerical simulations and comparisons with real-world cholera data from Yemen.The results confirm the reliability and practical applicability of the model,providing strong theoretical and empirical support for the approach.展开更多
In this paper, we investigate some new traveling wave solutions to Vakhnenko-Parkes equation via three modified mathematical methods. The derived solutions have been obtained including periodic and solitons solutions ...In this paper, we investigate some new traveling wave solutions to Vakhnenko-Parkes equation via three modified mathematical methods. The derived solutions have been obtained including periodic and solitons solutions in the form of trigonometric, hyperbolic, and rational function solutions. The graphical representations of some solutions by assigning particular values to the parameters under prescribed conditions in each solutions and comparing of solutions with those gained by other authors indicate that these employed techniques are more effective, efficient and applicable mathematical tools for solving nonlinear problems in applied science.展开更多
In the present article, we construct the exact traveling wave solutions of nonlinear PDEs in mathematical physics via the variant Boussinesq equations and the coupled KdV equations by using the extended mapping method...In the present article, we construct the exact traveling wave solutions of nonlinear PDEs in mathematical physics via the variant Boussinesq equations and the coupled KdV equations by using the extended mapping method and auxiliary equation method. This method is more powerful and will be used in further works to establish more entirely new solutions for other kinds of nonlinear partial differential equations arising in mathematical physics.展开更多
In this research work,we constructed the optical soliton solutions of nonlinear complex Kundu-Eckhaus(KE)equation with the help of modified mathematical method.We obtained the solutions in the form of dark solitons,br...In this research work,we constructed the optical soliton solutions of nonlinear complex Kundu-Eckhaus(KE)equation with the help of modified mathematical method.We obtained the solutions in the form of dark solitons,bright solitons and combined dark-bright solitons,travelling wave and periodic wave solutions with general coefficients.In our knowledge earlier reported results of the KE equation with specific coefficients.These obtained solutions are more useful in the development of optical fibers,dynamics of solitons,dynamics of adiabatic parameters,dynamics of fluid,problems of biomedical,industrial phenomena and many other branches.All calculations show that this technique is more powerful,effective,straightforward,and fruitfulness to study analytically other higher-order nonlinear complex PDEs involves in mathematical physics,quantum physics,Geo physics,fluid mechanics,hydrodynamics,mathematical biology,field of engineering and many other physical sciences.展开更多
This study presents a novelmethod to detect themedical application based on Quantum Computing(QC)and a few Machine Learning(ML)systems.QC has a primary advantage i.e.,it uses the impact of quantum parallelism to provi...This study presents a novelmethod to detect themedical application based on Quantum Computing(QC)and a few Machine Learning(ML)systems.QC has a primary advantage i.e.,it uses the impact of quantum parallelism to provide the consequences of prime factorization issue in a matter of seconds.So,this model is suggested for medical application only by recent researchers.A novel strategy i.e.,Quantum KernelMethod(QKM)is proposed in this paper for data prediction.In this QKM process,Linear Tunicate Swarm Algorithm(LTSA),the optimization technique is used to calculate the loss function initially and is aimed at medical data.The output of optimization is either 0 or 1 i.e.,odd or even in QC.From this output value,the data is identified according to the class.Meanwhile,the method also reduces time,saves cost and improves the efficiency by feature selection process i.e.,Filter method.After the features are extracted,QKM is deployed as a classification model,while the loss function is minimized by LTSA.The motivation of the minimal objective is to remain faster.However,some computations can be performed more efficiently by the proposed model.In testing,the test data was evaluated by minimal loss function.The outcomes were assessed in terms of accuracy,computational time,and so on.For this,databases like Lymphography,Dermatology,and Arrhythmia were used.展开更多
The present work introduces a mathematical model for ionic fluid that flows under the effect of both pulsating pressure and axial electromagnetic field. The fluid is treated as a Newtonian fluid applying Navier-Stokes...The present work introduces a mathematical model for ionic fluid that flows under the effect of both pulsating pressure and axial electromagnetic field. The fluid is treated as a Newtonian fluid applying Navier-Stokes equation. The fluid is considered as a neutral mixture of positive and negative ions. The effect of axial electric field is investigated to determine velocity profiles. Hydroelectric equation of the flow is deduced under dc and ac external electric field. Hence the effect of applied frequency （0-1 GHz） and amplitude （10-350 V/m） is illustrated. The ultimate goal is to approach the problem of EMF field interaction with blood flow. The applied pressure waveform is represented as such to simulate the systolic-diastolic behavior. Simulation was carried out using Maple software using blood plasma parameters; hence velocity profiles under various conditions are reported.展开更多
Saudi Arabia has become one of the leading top five countries based on the number of Snapchat users as of October 2018. In this project, we build a novel mathematical model to explore the future of Snapchat in general...Saudi Arabia has become one of the leading top five countries based on the number of Snapchat users as of October 2018. In this project, we build a novel mathematical model to explore the future of Snapchat in general and in Saudi Arabia particularly. The model incorporates the trend of “famous Snapchatters” that is highly observed in Saudi Arabia. The model is governed by a system of nonlinear differential equations. We analyze the system qualitatively and numerically. As a result, three equilibrium points are obtained. By considering their stability, we outline different possible scenarios for the future of Snapchat. Moreover, parameter analysis is performed to investigate key parameters in the model. Furthermore, an online survey is conducted to estimate the values for the parameters in the model to explore which scenario is likely to happen in Saudi Arabia.展开更多
In this paper, we derive and analyse rigorously a mathematical model of control strategies (screening, education, health care and immunization) of HCV in a community with inflow of infected immigrants. Both qualitativ...In this paper, we derive and analyse rigorously a mathematical model of control strategies (screening, education, health care and immunization) of HCV in a community with inflow of infected immigrants. Both qualitative and quantitative analysis of the model is performed with respect to stability of the disease free and endemic equilibria. The results show that the disease free equilibrium is locally stable at threshold parameter less than unity and unstable at threshold parameter greater than unity. Using Lyapunov method, endemic equilibrium is globally stable under certain conditions. Numerical simulation of the model is implemented to investigate the sensitivity of certain key parameters on the HCV model in a community with inflow of infected immigrants. However, analysis shows that screening, education, health care and immunization have the effect of reducing the transmission of the disease in the community.展开更多
A nonlinear mathematical model of vertical transmission of HIV/AIDS is proposed to study the effects of drug resistance in the spread of the disease. The study assumes that treatment leads to the evolution of drug res...A nonlinear mathematical model of vertical transmission of HIV/AIDS is proposed to study the effects of drug resistance in the spread of the disease. The study assumes that treatment leads to the evolution of drug resistance in some pockets of the population. We use traditional methods to determine conditions for existence and stability of disease-free and endemic equilibrium points of the model. The study showed that the burden of the disease may be reduced if the reproduction number is reduced below unity and may persist if the reproduction number is raised above unity. Furthermore, evolution of drug resistance due to treatment may change the cause of the epidemic.展开更多
Laminar boundary layer (BL), under adverse pressure gradient, can separate. The separated shear layer reattaches to form a laminar separation bubble. Such bubbles are usually observed on gas turbine blades, on low Rey...Laminar boundary layer (BL), under adverse pressure gradient, can separate. The separated shear layer reattaches to form a laminar separation bubble. Such bubbles are usually observed on gas turbine blades, on low Reynolds number wings and close to the leading edges of airfoils. Presence of bubbles has a weakening effect on the performance of a fluid device. The understanding of the prevailing mechanism of the separation bubble and ways to control it are essential for the efficient design of these devices. This is due to the significance of drag reduction in these various aerodynamic devices, such as gas turbines, re-entry space vehicles and airfoils. This study introduces a two-dimensional mathematical formulation of bubble formation after flow separation. The laminar BL equations with appropriate boundary conditions are dimensionalized using the Falkner-Skan transformation. Additionally, using the Keller-box method, the nonlinear system of partial differential equations (PDEs) is numerically solved. This study presents preliminary numerical results of bubble formation in low Mach numbers. These results reveal that after separation, a laminar bubble is formed in all studied cases, for Mach numbers, M = 0.2, 0.33 and 1.0. The flow after separation reverses close to the wall and finally reattaches downstream, in a new location. As the Mach number increases, this effect is more intense. After reattachment, the BL is again established in a lower energy level and the velocity field is substantially reduced, for all cases.展开更多
The study deals with the multi-choice mathematical programming problem, where the right hand side of the constraints is multi-choice in nature. However, the problem of multi-choice linear programming cannot be solved ...The study deals with the multi-choice mathematical programming problem, where the right hand side of the constraints is multi-choice in nature. However, the problem of multi-choice linear programming cannot be solved directly by standard linear or nonlinear programming techniques. The aim of this paper is to transform such problems to a standard mathematical linear programming problem. For each constraint, exactly one parameter value is selected out of a multiple number of parameter values. This process of selection can be established in different ways. In this paper, we present a new simple technique enabling us to handle such problem as a mixed integer linear programming problem and consequently solve them by using standard linear programming software. Our main aim depends on inserting a specific number of binary variables and using them to construct a linear combination which gives just one parameter among the multiple choice values for each choice of the values of the binary variables. A numerical example is presented to illustrate our analysis.展开更多
The nonlinear post-buckling response of functionally graded(FG)copper matrix plates enforced by graphene origami auxetic metamaterials(GOAMs)is investigated in the currentwork.The auxeticmaterial properties of the pla...The nonlinear post-buckling response of functionally graded(FG)copper matrix plates enforced by graphene origami auxetic metamaterials(GOAMs)is investigated in the currentwork.The auxeticmaterial properties of the plate are controlled by graphene content and the degree of origami folding,which are graded across the thickness of the plate.Thematerial properties of the GOAM plate are evaluated using genetic micro-mechanicalmodels.Governing nonlinear eigenvalue problems for the post-buckling response of the GOAM composite plate are derived using the virtual work principle and a four-variable nonlinear shear deformation theory.A novel differential quadrature method(DQM)algorithm is developed to solve the nonlinear eigenvalue problem.Detailed parametric studies are presented to explore the effects of graphene content,folding degree,and GO distribution patterns on the post-buckling responses of GOAM plates.Results show that high tunability in post-buckling characteristics can be achieved by using GOAM.FunctionallyGradedGraphene OrigamiAuxeticMetamaterials(FG-GOAM)plates can be used in aerospace structures to improve their structural performance and response.展开更多
The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,w...The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,which has significant applications in heat exchangers and engineering devices.To optimize heat transfer,a liquid film of Cu and TiO_(2)hybrid nanofluid behind a stretching sheet in a variable porous medium is being considered due to its importance.The nature of the fluid is considered time-dependent and the thickness of the liquid film is measured variable adjustable with the variable porous space and favorable for the uniform flow of the liquid film.The solution of the problem is acquired using the homotopy analysis method HAM,and the artificial neural network ANN is applied to obtain detailed information in the form of error estimation and validations using the fitting curve analysis.HAM data is utilized to train the ANN in this study,which uses Cu and TiO_(2)hybrid nanofluids in a variable porous space for unsteady thin film flow,and it is used to train the ANN.The results indicate that Cu and TiO_(2)play a greater role in boosting the rate.展开更多
A new extended distribution called the Odd Exponential Generalized Exponential-Exponential distribution(EOEGE-E)is proposed based on generalization of the odd generalized exponential family(OEGE-E).The statistical pro...A new extended distribution called the Odd Exponential Generalized Exponential-Exponential distribution(EOEGE-E)is proposed based on generalization of the odd generalized exponential family(OEGE-E).The statistical properties of the proposed distribution are derived.The study evaluates the accuracy of six estimation methods under complete samples.Estimation techniques include maximumlikelihood,ordinary least squares,weighted least squares,maximumproduct of spacing,Cramer vonMises,and Anderson-Darling methods.Twomethods of estimation for the involved parameters are considered based on progressively type Ⅱ censored data(PTⅡC).These methods are maximum likelihood and maximum product of spacing.The proposed distribution’s effectiveness was evaluated using different data sets from various fields.The proposed distribution provides a better fit for these datasets than existing probability distributions.展开更多
While the significant role of technological innovation in promoting renewable energy has been extensively explored in the literature,limited attention has been paid to the impact of energy patents,particularly clean e...While the significant role of technological innovation in promoting renewable energy has been extensively explored in the literature,limited attention has been paid to the impact of energy patents,particularly clean energy patents and fossil fuel patents.This study pioneers an investigation into the effects of energy patents and energy prices on renewable energy consumption.The study utilizes data from 2000Q1 to 2023Q4 and,due to the nonlinear nature of the series,applies wavelet quantile-based methods.Specifically,it introduces the wavelet quantile cointegration approach to evaluate cointegration across different quantiles and time horizons,along with the wavelet quantile-on-quantile regression method.The results confirm cointegration across different periods and quantiles,highlighting the significant relationships between energy patents,economic factors,and renewable energy consumption.Furthermore,we found that fossil energy patents negatively affect renewable energy consumption,while clean energy patents have a similar but weaker effect,especially in the short term.In addition,higher energy prices promote renewable energy adoption while economic growth positively influences renewable energy consumption,particularly in the short term.The study formulates specific policies based on these findings.展开更多
This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro...This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel,aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios.The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution,utilizing a comprehensive numerical approach.Employing a combination of mathematical modeling techniques,including similarity transformation,this investigation transforms complex partial differential equations into more manageable ordinary ones,subsequently solving them using the homotopy perturbation method.By analyzing the obtained solutions and presenting them graphically,alongside detailed analysis,the study sheds light on the pivotal role of significant parameters in shaping fluid movement and energy distribution.Noteworthy observations reveal a substantial increase in fluid velocity with escalating magnetic parameters,while conversely,a contrasting trend emerges in the temperature distribution,highlighting the intricate relationship between magnetic effects,flow dynamics,and thermal behavior in non-Newtonian fluids.Further,the suction velocity enhance both the local skin friction and Nusselt numbers,whereas theWeissenberg number reduces them,opposite to the effect of the power-law index.展开更多
This comprehensive research examines the dynamics of magnetohydrodynamic(MHD)flow and heat transfer within a couple stress fluid.The investigation specifically focuses on the fluid’s behavior over a vertical stretchi...This comprehensive research examines the dynamics of magnetohydrodynamic(MHD)flow and heat transfer within a couple stress fluid.The investigation specifically focuses on the fluid’s behavior over a vertical stretching sheet embedded within a porous medium,providing valuable insights into the complex interactions between fluid mechanics,thermal transport,and magnetic fields.This study accounts for the significant impact of heat generation and thermal radiation,crucial factors for enhancing heat transfer efficiency in various industrial and technological contexts.The research employs mathematical techniques to simplify complex partial differential equations(PDEs)governing fluid flow and heat transfer.Specifically,suitable similarity transformations are applied to convert the PDEs into a more manageable system of ordinary differential equations(ODEs).The homotopy perturbation method(HPM)is employed to derive approximate analytical solutions for the problem.The influences of key parameters,such as magnetic field strength,heat generation,thermal radiation,porosity,and couple stress,on velocity and temperature profiles are analyzed and discussed.Findings indicate that the mixed convection parameter positively affects flow velocity,while the magnetic field parameter significantly alters the flow dynamics,exhibiting an inverse relationship.Further,this type of flow behavior model is relevant to real-world systems like cooling of nuclear reactors and oil extraction through porous formations,where magnetic and thermal effects are significant.展开更多
This study numerically investigates inclined magneto-hydrodynamic natural convection in a porous cavity filled with nanofluid containing gyrotactic microorganisms.The governing equations are nondimensionalized and sol...This study numerically investigates inclined magneto-hydrodynamic natural convection in a porous cavity filled with nanofluid containing gyrotactic microorganisms.The governing equations are nondimensionalized and solved using the finite volume method.The simulations examine the impact of key parameters such as heat source length and position,Peclet number,porosity,and heat generation/absorption on flow patterns,temperature distribution,concentration profiles,and microorganism rotation.Results indicate that extending the heat source length enhances convective currents and heat transfer efficiency,while optimizing the heat source position reduces entropy generation.Higher Peclet numbers amplify convective currents and microorganism distribution complexity.Variations in porosity and heat generation/absorption significantly influence flow dynamics.Additionally,the artificial neural network model reliably predicts the mean Nusselt and Sherwood numbers(Nu&Sh),demonstrating its effectiveness for such analyses.The simulation results reveal that increasing the heat source length significantly enhances heat transfer,as evidenced by a 15%increase in the mean Nusselt number.展开更多
Traffic congestion plays a significant role in intelligent transportation systems(ITS)due to rapid urbanization and increased vehicle concentration.The congestion is dependent on multiple factors,such as limited road ...Traffic congestion plays a significant role in intelligent transportation systems(ITS)due to rapid urbanization and increased vehicle concentration.The congestion is dependent on multiple factors,such as limited road occupancy and vehicle density.Therefore,the transportation system requires an effective prediction model to reduce congestion issues in a dynamic environment.Conventional prediction systems face difficulties in identifying highly congested areas,which leads to reduced prediction accuracy.The problem is addressed by integrating Graph Neural Networks(GNN)with the Lion Swarm Optimization(LSO)framework to tackle the congestion prediction problem.Initially,the traffic information is collected and processed through a normalization process to scale the data and mitigate issues of overfitting and high dimensionality.Then,the traffic flow and temporal characteristic features are extracted to identify the connectivity of the road segment.From the connectivity and node relationship graph,modeling improves the overall prediction accuracy.During the analysis,the lion swarm optimization process utilizes the concepts of exploration and exploitation to understand the complex traffic dependencies,which helps predict high congestion on roads with minimal deviation errors.There are three core optimization phases:roaming,hunting,and migration,which enable the framework to make dynamic adjustments to enhance the predictions.The framework’s efficacy is evaluated using benchmark datasets,where the proposed work achieves 99.2%accuracy and minimizes the prediction deviation value by up to 2.5%compared to other methods.With the new framework,there was a more accurate prediction of realtime congestion,lower computational cost,and improved regulation of traffic flow.This system is easily implemented in intelligent transportation systems,smart cities,and self-driving cars,providing a robust and scalable solution for future traffic management.展开更多
Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution g...Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution grids.This study measures the effectiveness of the Puma optimizer(PO)algorithm in parameter estimation of PSC(perovskite solar cells)dynamic models with hysteresis consideration considering the electric field effects on operation.The models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs accurately.The PO optimizes the proposed modified triple diode model(TDM)with a variable voltage capacitor and resistances(VVCARs)considering the hysteresis behavior.The suggested PO algorithm contrasts with other wellknown optimizers from the literature to demonstrate its superiority.The results emphasize that the PO realizes a lower RMSE(Root mean square errors),which proves its capability and efficacy in parameter extraction for the models.The statistical results emphasize the efficiency and supremacy of the proposed PO compared to the other well-known competing optimizers.The convergence rates show good,fast,and stable convergence rates with lower RMSE via PO compared to the other five competitive optimizers.Moreover,the lowermean realized via the PO optimizer is illustrated by the box plot for all optimizers.展开更多
文摘This study introduces a novel mathematical model to describe the progression of cholera by integrating fractional derivatives with both singular and non-singular kernels alongside stochastic differential equations over four distinct time intervals.The model incorporates three key fractional derivatives:the Caputo-Fabrizio fractional derivative with a non-singular kernel,the Caputo proportional constant fractional derivative with a singular kernel,and the Atangana-Baleanu fractional derivative with a non-singular kernel.We analyze the stability of the core model and apply various numerical methods to approximate the proposed crossover model.To achieve this,the approximation of Caputo proportional constant fractional derivative with Grünwald-Letnikov nonstandard finite difference method is used for the deterministic model with a singular kernel,while the Toufik-Atangana method is employed for models involving a non-singular Mittag-Leffler kernel.Additionally,the integral Caputo-Fabrizio approximation and a two-step Lagrange polynomial are utilized to approximate the model with a non-singular exponential decay kernel.For the stochastic component,the Milstein method is implemented to approximate the stochastic differential equations.The stability and effectiveness of the proposed model and methodologies are validated through numerical simulations and comparisons with real-world cholera data from Yemen.The results confirm the reliability and practical applicability of the model,providing strong theoretical and empirical support for the approach.
文摘In this paper, we investigate some new traveling wave solutions to Vakhnenko-Parkes equation via three modified mathematical methods. The derived solutions have been obtained including periodic and solitons solutions in the form of trigonometric, hyperbolic, and rational function solutions. The graphical representations of some solutions by assigning particular values to the parameters under prescribed conditions in each solutions and comparing of solutions with those gained by other authors indicate that these employed techniques are more effective, efficient and applicable mathematical tools for solving nonlinear problems in applied science.
文摘In the present article, we construct the exact traveling wave solutions of nonlinear PDEs in mathematical physics via the variant Boussinesq equations and the coupled KdV equations by using the extended mapping method and auxiliary equation method. This method is more powerful and will be used in further works to establish more entirely new solutions for other kinds of nonlinear partial differential equations arising in mathematical physics.
文摘In this research work,we constructed the optical soliton solutions of nonlinear complex Kundu-Eckhaus(KE)equation with the help of modified mathematical method.We obtained the solutions in the form of dark solitons,bright solitons and combined dark-bright solitons,travelling wave and periodic wave solutions with general coefficients.In our knowledge earlier reported results of the KE equation with specific coefficients.These obtained solutions are more useful in the development of optical fibers,dynamics of solitons,dynamics of adiabatic parameters,dynamics of fluid,problems of biomedical,industrial phenomena and many other branches.All calculations show that this technique is more powerful,effective,straightforward,and fruitfulness to study analytically other higher-order nonlinear complex PDEs involves in mathematical physics,quantum physics,Geo physics,fluid mechanics,hydrodynamics,mathematical biology,field of engineering and many other physical sciences.
基金This research work was funded by Institutional fund projects under Grant No.(IFPHI-038-156-2020)Therefore,authors gratefully acknowledge technical and financial support from Ministry of Education and King Abdulaziz University,DSR,Jeddah,Saudi Arabia.
文摘This study presents a novelmethod to detect themedical application based on Quantum Computing(QC)and a few Machine Learning(ML)systems.QC has a primary advantage i.e.,it uses the impact of quantum parallelism to provide the consequences of prime factorization issue in a matter of seconds.So,this model is suggested for medical application only by recent researchers.A novel strategy i.e.,Quantum KernelMethod(QKM)is proposed in this paper for data prediction.In this QKM process,Linear Tunicate Swarm Algorithm(LTSA),the optimization technique is used to calculate the loss function initially and is aimed at medical data.The output of optimization is either 0 or 1 i.e.,odd or even in QC.From this output value,the data is identified according to the class.Meanwhile,the method also reduces time,saves cost and improves the efficiency by feature selection process i.e.,Filter method.After the features are extracted,QKM is deployed as a classification model,while the loss function is minimized by LTSA.The motivation of the minimal objective is to remain faster.However,some computations can be performed more efficiently by the proposed model.In testing,the test data was evaluated by minimal loss function.The outcomes were assessed in terms of accuracy,computational time,and so on.For this,databases like Lymphography,Dermatology,and Arrhythmia were used.
文摘The present work introduces a mathematical model for ionic fluid that flows under the effect of both pulsating pressure and axial electromagnetic field. The fluid is treated as a Newtonian fluid applying Navier-Stokes equation. The fluid is considered as a neutral mixture of positive and negative ions. The effect of axial electric field is investigated to determine velocity profiles. Hydroelectric equation of the flow is deduced under dc and ac external electric field. Hence the effect of applied frequency （0-1 GHz） and amplitude （10-350 V/m） is illustrated. The ultimate goal is to approach the problem of EMF field interaction with blood flow. The applied pressure waveform is represented as such to simulate the systolic-diastolic behavior. Simulation was carried out using Maple software using blood plasma parameters; hence velocity profiles under various conditions are reported.
文摘Saudi Arabia has become one of the leading top five countries based on the number of Snapchat users as of October 2018. In this project, we build a novel mathematical model to explore the future of Snapchat in general and in Saudi Arabia particularly. The model incorporates the trend of “famous Snapchatters” that is highly observed in Saudi Arabia. The model is governed by a system of nonlinear differential equations. We analyze the system qualitatively and numerically. As a result, three equilibrium points are obtained. By considering their stability, we outline different possible scenarios for the future of Snapchat. Moreover, parameter analysis is performed to investigate key parameters in the model. Furthermore, an online survey is conducted to estimate the values for the parameters in the model to explore which scenario is likely to happen in Saudi Arabia.
文摘In this paper, we derive and analyse rigorously a mathematical model of control strategies (screening, education, health care and immunization) of HCV in a community with inflow of infected immigrants. Both qualitative and quantitative analysis of the model is performed with respect to stability of the disease free and endemic equilibria. The results show that the disease free equilibrium is locally stable at threshold parameter less than unity and unstable at threshold parameter greater than unity. Using Lyapunov method, endemic equilibrium is globally stable under certain conditions. Numerical simulation of the model is implemented to investigate the sensitivity of certain key parameters on the HCV model in a community with inflow of infected immigrants. However, analysis shows that screening, education, health care and immunization have the effect of reducing the transmission of the disease in the community.
文摘A nonlinear mathematical model of vertical transmission of HIV/AIDS is proposed to study the effects of drug resistance in the spread of the disease. The study assumes that treatment leads to the evolution of drug resistance in some pockets of the population. We use traditional methods to determine conditions for existence and stability of disease-free and endemic equilibrium points of the model. The study showed that the burden of the disease may be reduced if the reproduction number is reduced below unity and may persist if the reproduction number is raised above unity. Furthermore, evolution of drug resistance due to treatment may change the cause of the epidemic.
文摘Laminar boundary layer (BL), under adverse pressure gradient, can separate. The separated shear layer reattaches to form a laminar separation bubble. Such bubbles are usually observed on gas turbine blades, on low Reynolds number wings and close to the leading edges of airfoils. Presence of bubbles has a weakening effect on the performance of a fluid device. The understanding of the prevailing mechanism of the separation bubble and ways to control it are essential for the efficient design of these devices. This is due to the significance of drag reduction in these various aerodynamic devices, such as gas turbines, re-entry space vehicles and airfoils. This study introduces a two-dimensional mathematical formulation of bubble formation after flow separation. The laminar BL equations with appropriate boundary conditions are dimensionalized using the Falkner-Skan transformation. Additionally, using the Keller-box method, the nonlinear system of partial differential equations (PDEs) is numerically solved. This study presents preliminary numerical results of bubble formation in low Mach numbers. These results reveal that after separation, a laminar bubble is formed in all studied cases, for Mach numbers, M = 0.2, 0.33 and 1.0. The flow after separation reverses close to the wall and finally reattaches downstream, in a new location. As the Mach number increases, this effect is more intense. After reattachment, the BL is again established in a lower energy level and the velocity field is substantially reduced, for all cases.
文摘The study deals with the multi-choice mathematical programming problem, where the right hand side of the constraints is multi-choice in nature. However, the problem of multi-choice linear programming cannot be solved directly by standard linear or nonlinear programming techniques. The aim of this paper is to transform such problems to a standard mathematical linear programming problem. For each constraint, exactly one parameter value is selected out of a multiple number of parameter values. This process of selection can be established in different ways. In this paper, we present a new simple technique enabling us to handle such problem as a mixed integer linear programming problem and consequently solve them by using standard linear programming software. Our main aim depends on inserting a specific number of binary variables and using them to construct a linear combination which gives just one parameter among the multiple choice values for each choice of the values of the binary variables. A numerical example is presented to illustrate our analysis.
文摘The nonlinear post-buckling response of functionally graded(FG)copper matrix plates enforced by graphene origami auxetic metamaterials(GOAMs)is investigated in the currentwork.The auxeticmaterial properties of the plate are controlled by graphene content and the degree of origami folding,which are graded across the thickness of the plate.Thematerial properties of the GOAM plate are evaluated using genetic micro-mechanicalmodels.Governing nonlinear eigenvalue problems for the post-buckling response of the GOAM composite plate are derived using the virtual work principle and a four-variable nonlinear shear deformation theory.A novel differential quadrature method(DQM)algorithm is developed to solve the nonlinear eigenvalue problem.Detailed parametric studies are presented to explore the effects of graphene content,folding degree,and GO distribution patterns on the post-buckling responses of GOAM plates.Results show that high tunability in post-buckling characteristics can be achieved by using GOAM.FunctionallyGradedGraphene OrigamiAuxeticMetamaterials(FG-GOAM)plates can be used in aerospace structures to improve their structural performance and response.
文摘The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,which has significant applications in heat exchangers and engineering devices.To optimize heat transfer,a liquid film of Cu and TiO_(2)hybrid nanofluid behind a stretching sheet in a variable porous medium is being considered due to its importance.The nature of the fluid is considered time-dependent and the thickness of the liquid film is measured variable adjustable with the variable porous space and favorable for the uniform flow of the liquid film.The solution of the problem is acquired using the homotopy analysis method HAM,and the artificial neural network ANN is applied to obtain detailed information in the form of error estimation and validations using the fitting curve analysis.HAM data is utilized to train the ANN in this study,which uses Cu and TiO_(2)hybrid nanofluids in a variable porous space for unsteady thin film flow,and it is used to train the ANN.The results indicate that Cu and TiO_(2)play a greater role in boosting the rate.
文摘A new extended distribution called the Odd Exponential Generalized Exponential-Exponential distribution(EOEGE-E)is proposed based on generalization of the odd generalized exponential family(OEGE-E).The statistical properties of the proposed distribution are derived.The study evaluates the accuracy of six estimation methods under complete samples.Estimation techniques include maximumlikelihood,ordinary least squares,weighted least squares,maximumproduct of spacing,Cramer vonMises,and Anderson-Darling methods.Twomethods of estimation for the involved parameters are considered based on progressively type Ⅱ censored data(PTⅡC).These methods are maximum likelihood and maximum product of spacing.The proposed distribution’s effectiveness was evaluated using different data sets from various fields.The proposed distribution provides a better fit for these datasets than existing probability distributions.
文摘While the significant role of technological innovation in promoting renewable energy has been extensively explored in the literature,limited attention has been paid to the impact of energy patents,particularly clean energy patents and fossil fuel patents.This study pioneers an investigation into the effects of energy patents and energy prices on renewable energy consumption.The study utilizes data from 2000Q1 to 2023Q4 and,due to the nonlinear nature of the series,applies wavelet quantile-based methods.Specifically,it introduces the wavelet quantile cointegration approach to evaluate cointegration across different quantiles and time horizons,along with the wavelet quantile-on-quantile regression method.The results confirm cointegration across different periods and quantiles,highlighting the significant relationships between energy patents,economic factors,and renewable energy consumption.Furthermore,we found that fossil energy patents negatively affect renewable energy consumption,while clean energy patents have a similar but weaker effect,especially in the short term.In addition,higher energy prices promote renewable energy adoption while economic growth positively influences renewable energy consumption,particularly in the short term.The study formulates specific policies based on these findings.
文摘This study rigorously examines the interplay between viscous dissipation,magnetic effects,and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel,aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios.The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution,utilizing a comprehensive numerical approach.Employing a combination of mathematical modeling techniques,including similarity transformation,this investigation transforms complex partial differential equations into more manageable ordinary ones,subsequently solving them using the homotopy perturbation method.By analyzing the obtained solutions and presenting them graphically,alongside detailed analysis,the study sheds light on the pivotal role of significant parameters in shaping fluid movement and energy distribution.Noteworthy observations reveal a substantial increase in fluid velocity with escalating magnetic parameters,while conversely,a contrasting trend emerges in the temperature distribution,highlighting the intricate relationship between magnetic effects,flow dynamics,and thermal behavior in non-Newtonian fluids.Further,the suction velocity enhance both the local skin friction and Nusselt numbers,whereas theWeissenberg number reduces them,opposite to the effect of the power-law index.
文摘This comprehensive research examines the dynamics of magnetohydrodynamic(MHD)flow and heat transfer within a couple stress fluid.The investigation specifically focuses on the fluid’s behavior over a vertical stretching sheet embedded within a porous medium,providing valuable insights into the complex interactions between fluid mechanics,thermal transport,and magnetic fields.This study accounts for the significant impact of heat generation and thermal radiation,crucial factors for enhancing heat transfer efficiency in various industrial and technological contexts.The research employs mathematical techniques to simplify complex partial differential equations(PDEs)governing fluid flow and heat transfer.Specifically,suitable similarity transformations are applied to convert the PDEs into a more manageable system of ordinary differential equations(ODEs).The homotopy perturbation method(HPM)is employed to derive approximate analytical solutions for the problem.The influences of key parameters,such as magnetic field strength,heat generation,thermal radiation,porosity,and couple stress,on velocity and temperature profiles are analyzed and discussed.Findings indicate that the mixed convection parameter positively affects flow velocity,while the magnetic field parameter significantly alters the flow dynamics,exhibiting an inverse relationship.Further,this type of flow behavior model is relevant to real-world systems like cooling of nuclear reactors and oil extraction through porous formations,where magnetic and thermal effects are significant.
基金Dean ship of Scientific Research at King Khalid University,Abha,Saudi Arabia,for funding this work through the Research Group Project(Grant No.RGP.2/610/45)funded by the Princess Nourah bint Abdulrahman University Researchers Supporting Project(Grant No.PNURSP2024R102),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘This study numerically investigates inclined magneto-hydrodynamic natural convection in a porous cavity filled with nanofluid containing gyrotactic microorganisms.The governing equations are nondimensionalized and solved using the finite volume method.The simulations examine the impact of key parameters such as heat source length and position,Peclet number,porosity,and heat generation/absorption on flow patterns,temperature distribution,concentration profiles,and microorganism rotation.Results indicate that extending the heat source length enhances convective currents and heat transfer efficiency,while optimizing the heat source position reduces entropy generation.Higher Peclet numbers amplify convective currents and microorganism distribution complexity.Variations in porosity and heat generation/absorption significantly influence flow dynamics.Additionally,the artificial neural network model reliably predicts the mean Nusselt and Sherwood numbers(Nu&Sh),demonstrating its effectiveness for such analyses.The simulation results reveal that increasing the heat source length significantly enhances heat transfer,as evidenced by a 15%increase in the mean Nusselt number.
基金Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2025-02-01641)。
文摘Traffic congestion plays a significant role in intelligent transportation systems(ITS)due to rapid urbanization and increased vehicle concentration.The congestion is dependent on multiple factors,such as limited road occupancy and vehicle density.Therefore,the transportation system requires an effective prediction model to reduce congestion issues in a dynamic environment.Conventional prediction systems face difficulties in identifying highly congested areas,which leads to reduced prediction accuracy.The problem is addressed by integrating Graph Neural Networks(GNN)with the Lion Swarm Optimization(LSO)framework to tackle the congestion prediction problem.Initially,the traffic information is collected and processed through a normalization process to scale the data and mitigate issues of overfitting and high dimensionality.Then,the traffic flow and temporal characteristic features are extracted to identify the connectivity of the road segment.From the connectivity and node relationship graph,modeling improves the overall prediction accuracy.During the analysis,the lion swarm optimization process utilizes the concepts of exploration and exploitation to understand the complex traffic dependencies,which helps predict high congestion on roads with minimal deviation errors.There are three core optimization phases:roaming,hunting,and migration,which enable the framework to make dynamic adjustments to enhance the predictions.The framework’s efficacy is evaluated using benchmark datasets,where the proposed work achieves 99.2%accuracy and minimizes the prediction deviation value by up to 2.5%compared to other methods.With the new framework,there was a more accurate prediction of realtime congestion,lower computational cost,and improved regulation of traffic flow.This system is easily implemented in intelligent transportation systems,smart cities,and self-driving cars,providing a robust and scalable solution for future traffic management.
基金supported via funding from Prince Sattam Bin Abdulaziz University project number(PSAU/2025/R/1446).
文摘Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution grids.This study measures the effectiveness of the Puma optimizer(PO)algorithm in parameter estimation of PSC(perovskite solar cells)dynamic models with hysteresis consideration considering the electric field effects on operation.The models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs accurately.The PO optimizes the proposed modified triple diode model(TDM)with a variable voltage capacitor and resistances(VVCARs)considering the hysteresis behavior.The suggested PO algorithm contrasts with other wellknown optimizers from the literature to demonstrate its superiority.The results emphasize that the PO realizes a lower RMSE(Root mean square errors),which proves its capability and efficacy in parameter extraction for the models.The statistical results emphasize the efficiency and supremacy of the proposed PO compared to the other well-known competing optimizers.The convergence rates show good,fast,and stable convergence rates with lower RMSE via PO compared to the other five competitive optimizers.Moreover,the lowermean realized via the PO optimizer is illustrated by the box plot for all optimizers.
