Series solution of typhoid fever model using differential transform method / Olumuyiwa James Peter ... [et al.]

This paper presents an analysis of PSIuIeTR type model, which are used to study the transmission dynamics of typhoid fever diseases in a population. Basic idea of typhoid fever disease transmission using compartmental modeling is discussed. Differential Transformation Method (DTM) is discussed in de...

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Bibliographic Details
Main Authors: Peter, Olumuyiwa James (Author), Akinduko, Oluwaseun (Author), Ishola, Christie (Author), Afolabi, Ahmed (Author), Ganiyu, Afees (Author)
Format: Article
Language:English
Published: Universiti Teknologi MARA Press (Penerbit UiTM), 2018.
Subjects:
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100 1 0 |a Peter, Olumuyiwa James  |e author 
700 1 0 |a Akinduko, Oluwaseun  |e author 
700 1 0 |a Ishola, Christie  |e author 
700 1 0 |a Afolabi, Ahmed  |e author 
700 1 0 |a Ganiyu, Afees  |e author 
245 0 0 |a Series solution of typhoid fever model using differential transform method / Olumuyiwa James Peter ... [et al.] 
260 |b Universiti Teknologi MARA Press (Penerbit UiTM),   |c 2018. 
856 |z Get fulltext  |u https://ir.uitm.edu.my/id/eprint/43156/1/43156.pdf 
856 |z View Fulltext in UiTM IR  |u https://ir.uitm.edu.my/id/eprint/43156/ 
520 |a This paper presents an analysis of PSIuIeTR type model, which are used to study the transmission dynamics of typhoid fever diseases in a population. Basic idea of typhoid fever disease transmission using compartmental modeling is discussed. Differential Transformation Method (DTM) is discussed in detail, which is used to compute the series solution of the non-linear system of differential equation governing the model equations. The validity of the (DTM) in solving the proposed model is established by classical fourth-order Runge-Kutta method which is implemented in Maple 18. Graphical results confirm that (DTM) is in good agreement with RK-4 and this produced correctly same behaviour of the model, thus validating the efficiency and accuracy of (DTM) in finding the series solution of an epidemic model. 
546 |a en 
650 0 4 |a Neural networks (Computer science). Data processing 
650 0 4 |a Biomedical engineering 
650 0 4 |a Computer applications to medicine. Medical informatics 
655 7 |a Article