Research Article Fractional-Stochastic Solutions for the Generalized (2+1 )-Dimensional Nonlinear Conformable Fractional Schrödinger System Forced by Multiplicative Brownian Motion Sahar Albosaily , 1 Wael W. Mohammed , 1,2 Ekram E. Ali , 1 R. Sidaoui , 1 E. S. Aly , 3 and M. El-Morshedy 4,5 1 Department of Mathematics, Faculty of Science, University of Ha’il, Ha’il 2440, Saudi Arabia 2 Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt 3 Mathematics Department, Faculty of Science, Jazan University, Jazan 45142, Saudi Arabia 4 Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia 5 Department of Statistics and Computer Science, Faculty of Science, Mansoura University, Mansoura 35516, Egypt Correspondence should be addressed to Wael W. Mohammed; wael.mohammed@mans.edu.eg Received 13 May 2022; Revised 31 May 2022; Accepted 6 June 2022; Published 19 June 2022 Academic Editor: Yusuf Gurefe Copyright © 2022 Sahar Albosaily et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In this paper, the (2+1)-dimensional nonlinear conformable fractional stochastic Schrödinger system (NCFSSS) generated by the multiplicative Brownian motion is treated. To get new rational, trigonometric, hyperbolic, and elliptic stochastic solutions, we use two different methods: the sine-cosine and the Jacobi elliptic function methods. Moreover, we use the MATLAB tools to plot our figures to introduce a variety of 2D and 3D graphs to highlight the effect of the multiplicative noise on the exact solutions of the NCFSSS. Finally, we illustrate that the multiplicative Brownian motion stabilizes the solutions of NCFSSS a round zero. 1. Introduction Stochastic partial differential equations (SPDEs) can be used to represent a wide range of complicated nonlinear physical processes. These kinds of equations appear in a variety of areas including physics, finance, climate dynamics, chemis- try, biology, geophysical, engineering, and other fields [1–3]. On the other side, fractional partial differential equations (FPDEs) have gotten a lot of interest because they may illus- trate the fundamental components underlying real-world issues. They have been seen in a number of physical phe- nomena, such as viscoelastic materials with relaxation and creeping functions, the motion of a heavy meager surface in a Newtonian fluid, and relapse subordinate dissipative occupancy of components. As a result, FPDEs are employed in a range of fields, including predicting, describing, and modeling the mechanisms engaged in finance, polymeric materials, a kinematic model of neutron points, engineering, electrical circuits, solid-state physics, optical fibers, chemical kinematics, biogenetics, plasma physics, physics of con- densed matter, meteorology, electromagnetic, elasticity, and oceanic spectacles [4–9]. The exact solutions of PDEs are important in nonlinear science. As a result, various analytical techniques, such as tanh-sech [10, 11], Darboux transformation [12], sine-cosine [13, 14], extended simple equation [15], extended sinh- Gordon equation expansion [16], F-expansion [17], Kudrya- shov technique [18], generalized Kudryashov [19–21], exp ð −ϕðςÞÞ-expansion [22], ðG′ /GÞ-expansion [23–25], Hirota’s function [26], perturbation [5, 27], the Jacobi elliptic function [28, 29], and Riccati-Bernoulli sub-ODE [30], have been cre- ated to deal with these types of equations. Hindawi Journal of Function Spaces Volume 2022, Article ID 6306220, 8 pages https://doi.org/10.1155/2022/6306220