2022
DOI: 10.1002/zamm.202100199
|View full text |Cite
|
Sign up to set email alerts
|

Exact solutions of the stochastic Maccari system forced by multiplicative noise

Abstract: In the Itô sense, we look at the stochastic Maccari system (SMS) with multiplicative noise. To generate new analytical stochastic solutions, we use three separate techniques including sine-cosine, Riccati-Bernoulli sub-ODE, and semi-inverse.Such solutions are critical for comprehending some fascinating and complex physical phenomena. In addition, some results from earlier studies are generalized. Furthermore, we investigate the impact of stochastic term on the exact solutions of the SMS.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4

Citation Types

0
3
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 12 publications
(4 citation statements)
references
References 33 publications
(54 reference statements)
0
3
0
Order By: Relevance
“…These recent advancements mark a notable breakthrough in the field, as researchers have successfully obtained exact solutions for a subset of SDEs. The exploration of exact solutions in the realm of SDEs continues to enhance our knowledge and pave the way for further advancements in stochastic analysis and related disciplines [11,12,13].…”
Section: Introductionmentioning
confidence: 99%
“…These recent advancements mark a notable breakthrough in the field, as researchers have successfully obtained exact solutions for a subset of SDEs. The exploration of exact solutions in the realm of SDEs continues to enhance our knowledge and pave the way for further advancements in stochastic analysis and related disciplines [11,12,13].…”
Section: Introductionmentioning
confidence: 99%
“…These recent advancements mark a notable breakthrough in the field, as researchers have successfully obtained exact solutions for a subset of SDEs. The exploration of exact solutions in the realm of SDEs continues to enhance our knowledge and pave the way for further advancements in stochastic analysis and related disciplines [11,12,13].…”
Section: Introductionmentioning
confidence: 99%
“…The use of stochastic NEEs for developing mathematical models of complex processes is on the rise in many fields, including materials sciences, condensed matter climate, finance, information systems, electrical engineering, biophysics and physics system modeling [14,15]. In recent years, analytical solutions for some stochastic NEEs have been acquired, for example [16][17][18][19][20] and the references therein.…”
Section: Introductionmentioning
confidence: 99%