Numerical Solutions of the Second-Order One-Dimensional Telegraph Equation Based on Reproducing Kernel Hilbert Space Method

Inc, Mustafa; Akgül, Ali; Kılıçman, Adem

doi:10.1155/2013/768963

Cited by 26 publications

(17 citation statements)

References 23 publications

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“…The used regression analysis method in analysis of their results, the regression results showed significant relationships between malaria, rainfall and water bodies while other variables such as Human Development Index, temperature, population density and percent of cultivated areas were not significant. Teklehaimanot et al [7,8,9,10] used robust Poisson regression model to model the daily average number of cases in 10 districts of Ethiopia that was associated with rainfall, minimum temperature and maximum temperature as explanatory variable in a polynomial distributed lag model. To improve reliability and generalizability within similar climatic conditions, the districts were grouped into two climatic zones, hot and cold.…”

Section: Literature Reviewmentioning

confidence: 99%

Fitting Probability Distribution Function to Malaria Incidence Data

Mbete

Nyongesa

Rotich

2019

AJPAS

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Malaria remains a major infectious disease that affects millions of people. Once infected with Plasmodium parasites, a host can develop a broad range of clinical presentations, which result from complex interactions between factors derived from the host, the parasite and the environment. Malaria has historically been a very serious health problem and currently poses the most significant threat to the health of Masinde Muliro University of Science and Technology students, data shows that more than 70% percent of pediatric cases are due to malaria. Methodology: Hence, the study aimed to fit malaria incidences dataset for the period 1st January, 2013 to 31st December, 2015. Data on monthly malaria incidence was obtained from the Masinde Muliro University of Science and Technology health service. Gamma, Weibull and Lognormal Distributions were employed to fit the malaria incidence dataset using R-software. Results: High malaria incidences were observed in the months of August, September and November. AIC values results showed that lognormal distribution had the lowest AIC value of 185.9875 followed by the Gamma distribution with a value of 187.8815 and then the Weibull distribution with a value of 188.7271. This confirmed the lognormal distribution to be the best fitting distribution for the malaria incidence dataset Conclusion: The Poisson regression model did not accurately fit the data on malaria incidences due to over dispersion in the data but lognormal distribution was a better fit compared to gamma and Weibull distribution.

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Section: Literature Reviewmentioning

confidence: 99%

Fitting Probability Distribution Function to Malaria Incidence Data

Mbete

Nyongesa

Rotich

2019

AJPAS

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“…A transformations method can be used to get an exact solution to a differential equation. There are many methods which use transformation, Laplace transforms are commonly used in solving mathematical and physical problems which contains ordinary or partial differential equations with constant coefficients and integral equations as those problems are arising in the many branches of physics as electronic circuit analysis [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. But it takes too much time for solving by hand and in papers, These ODE can be analyzed.…”

Section: Introductionmentioning

confidence: 99%

On the Matlab Technique by Using Laplace Transform for Solving Second Order Ode With Initial Conditions Exactly

Faraj¹,

Ahmed²

2019

Matrix sci. math.

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In this paper Matlab technique has been presented that is approach to exact solution for second order ODE with constant coefficients and initial condition by using Laplace transformation. Matlab function has been constructed to estimate and compute exact solution of second order ordinary differential equations with initial conditions generally, the results of the program shows the elapsed time, exact solution and it's figures. KEYWORDSOrdinary differential equation, Matlab program, Laplace transform, Initial value problems.ℒ{ } + 3 ℒ{ } + 2 ℒ{ } = ℒ{cos( ) − − sin( ) − }, using the rules and for derivatives in definition (1.1), where ( ) = ℒ{ },

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“…Al e'damat applied analytical-numerical method for solving a class of two-point boundary value problems [14]. For more details see [15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Reproducing kernel Hilbert space method for solutions of a coefficient inverse problem for the kinetic equation

Akgül¹

2018

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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On the basis of a reproducing kernel Hilbert space, reproducing kernel functions for solving the coefficient inverse problem for the kinetic equation are given in this paper. Reproducing kernel functions found in the reproducing kernel Hilbert space imply that they can be considered for solving such inverse problems. We obtain approximate solutions by reproducing kernel functions. We show our results by a table. We prove the efficiency of the reproducing kernel Hilbert space method for solutions of a coefficient inverse problem for the kinetic equation.

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Numerical Solutions of the Second-Order One-Dimensional Telegraph Equation Based on Reproducing Kernel Hilbert Space Method

Cited by 26 publications

References 23 publications

Fitting Probability Distribution Function to Malaria Incidence Data

Fitting Probability Distribution Function to Malaria Incidence Data

On the Matlab Technique by Using Laplace Transform for Solving Second Order Ode With Initial Conditions Exactly

Reproducing kernel Hilbert space method for solutions of a coefficient inverse problem for the kinetic equation

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