Analysis of Random Difference Equations Using the Differential Transformation Method
MakaleAçık Erişim
Özet
The differential transformation method (DTM) is one of the best methods easily applied to linear and nonlinear difference equations with random coefficients. In this study, we apply the theorems related to the DTM to the given examples and investigate the behaviour of the approximate analytical solutions. The expected value, variance, coefficient of variation, and confidence intervals of the solutions of random difference equations obtained from discrete probability distributions such as uniform, geometric, Poisson, and binomial distributions will be calculated. Maple and MATLAB software packages are used to plot the solution graphs and also to interpret the solution behaviour.
Anahtar Kelimeler
RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/12767Resmi atıflarda kullanılan kalıcı adresTam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Şişman, Şeyma | |
| dc.contributor.author | Merdan, Mehmet | |
| dc.date.accessioned | 2026-10-22T10:20:31.300206968Z | |
| dc.date.available | 2026-10-22T10:20:31.300206968Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The differential transformation method (DTM) is one of the best methods easily applied to linear and nonlinear difference equations with random coefficients. In this study, we apply the theorems related to the DTM to the given examples and investigate the behaviour of the approximate analytical solutions. The expected value, variance, coefficient of variation, and confidence intervals of the solutions of random difference equations obtained from discrete probability distributions such as uniform, geometric, Poisson, and binomial distributions will be calculated. Maple and MATLAB software packages are used to plot the solution graphs and also to interpret the solution behaviour. | |
| dc.identifier.articlenumber | 2424880 | |
| dc.identifier.doi | 10.1155/2024/2424880 | |
| dc.identifier.eissn | 1687-0042 | |
| dc.identifier.issn | 1110-757X | |
| dc.identifier.scopus | 2-s2.0-85205880884 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/12767 | |
| dc.identifier.volume | 2024 | |
| dc.identifier.wos | WOS:001321351800001 | |
| dc.language.iso | en | |
| dc.publisher | Hindawi Limited | |
| dc.relation.ispartof | Journal of Applied Mathematics | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | difference equations | |
| dc.subject | differential equations | |
| dc.subject | differential transformation method | |
| dc.subject.classification | Mathematics, Applied | |
| dc.subject.classification | Mathematics, Interdisciplinary Applications | |
| dc.subject.classification | Mathematics | |
| dc.subject.other | Difference equations | |
| dc.subject.other | Linear transformations | |
| dc.subject.other | Nonlinear equations | |
| dc.subject.other | Poisson distribution | |
| dc.subject.other | Poisson equation | |
| dc.subject.other | Random processes | |
| dc.subject.other | Random variables | |
| dc.subject.other | Approximate analytical solutions | |
| dc.subject.other | Coefficients of variations | |
| dc.subject.other | Confidence interval | |
| dc.subject.other | Differential transformation | |
| dc.subject.other | Differential transformation method | |
| dc.subject.other | Expected values | |
| dc.subject.other | Linear difference equations | |
| dc.subject.other | Nonlinear difference equations | |
| dc.subject.other | Random coefficients | |
| dc.subject.other | Transformation methods | |
| dc.subject.other | MATLAB | |
| dc.title | Analysis of Random Difference Equations Using the Differential Transformation Method | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| rdl.citation.openalex | 0 | |
| rdl.citation.scopus | 0 | |
| rdl.citation.wos | 0 | |
| rdl.oa.status | gold | |
| rdl.oa.url | https://doi.org/10.1155/2024/2424880 | |
| rdl.source.index | SCOPUS | |
| rdl.source.index | WOS | |
| rdl.wos.index | Emerging Sources Citation Index (ESCI) |
