Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Vali Torkashvand"'
Autor:
Vali Torkashvand
Publikováno v:
Mathematics and Computational Sciences, Vol 5, Iss 3, Pp 80-92 (2024)
In this work,a fourth-order without-memory method is proposed that has a self-accelerator parameter.This method doesn’t need to compute a derivative function forsolving nonlinear equations.We have approximated the self-accelerator parameter andhave
Externí odkaz:
https://doaj.org/article/03b5aa5bb432422a937d1ced7590dcb2
Autor:
Vali Torkashvand
Publikováno v:
AUT Journal of Mathematics and Computing, Vol 6, Iss 1, Pp 81-93 (2024)
The adaptive technique enables us to achieve the highest efficiency index theoretically and practically. The idea of introducing an adaptive self-accelerator (via all the old information for Steffensen-type methods) is new and efficient to obtain the
Externí odkaz:
https://doaj.org/article/948bc8a0a9284de0a8c8340f14f33e71
Autor:
Vali Torkashvand
Publikováno v:
Journal of Numerical Analysis and Approximation Theory, Vol 50, Iss 1 (2021)
In this work, we have designed a family of with-memory methods with eighth-order convergence. We have used the weight function technique. The proposed methods have three parameters. Three self-accelerating parameters are calculated in each iterative
Externí odkaz:
https://doaj.org/article/ce1fe8947ce749e1851ea152d47df57f
Publikováno v:
Mathematics, Vol 10, Iss 9, p 1370 (2022)
In this paper, we first derive a family of iterative schemes with fourth order. A weight function is used to maintain its optimality. Then, we transform it into methods with several self-accelerating parameters to reach the highest possible convergen
Externí odkaz:
https://doaj.org/article/5f2351afe59647a28c9394fd52357d52
Publikováno v:
Proyecciones (Antofagasta). 39:1167-1189
We are devoted to the study of an iterative recursive Traub-Steffensen like method for approximating the simple roots of a nonlinear equation. Using the recursive technique, the R-order of convergence is increased from 4 to 8 without any new function
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ec7c793086b935327402f2ae97a32cf
https://doi.org/10.22199/issn.0717-6279-2020-05-0072
https://doi.org/10.22199/issn.0717-6279-2020-05-0072
Publikováno v:
Mathematical Sciences, Vol 13, Iss 1, Pp 1-20 (2018)
In this work, an adaptive method with memory is developed such that all previous information are applied. The importance of the proposed method can be seen because of the optimization in important effecting factors, i.e., least number of iterations s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1f5b0e64131f03f49a5f68bc03f31db
https://doi.org/10.1007/s40096-018-0272-2
https://doi.org/10.1007/s40096-018-0272-2
Autor:
Manochehr Kazemi, Vali Torkashvand
Publikováno v:
Computational Science and Its Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fff72b6ea7a156cf419c321f493f4ab8
https://doi.org/10.1201/9780429288739-6
https://doi.org/10.1201/9780429288739-6
