Results 191 to 200 of about 310,373 (322)

Unveiling New Perspectives on the Hirota–Maccari System With Multiplicative White Noise

open access: yesMathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In this study, we delve into the stochastic Hirota–Maccari system, which is subjected to multiplicative noise according to the Itô sense. The stochastic Hirota–Maccari system is significant for its ability to accurately model how stochastic affects nonlinear wave propagation, providing valuable insights into complex systems like fluid dynamics
Mohamed E. M. Alngar   +3 more
wiley   +1 more source

Analytical and Numerical Soliton Solutions of the Shynaray II‐A Equation Using the G′G,1G$$ \left(\frac{G^{\prime }}{G},\frac{1}{G}\right) $$‐Expansion Method and Regularization‐Based Neural Networks

open access: yesMathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT Nonlinear differential equations play a fundamental role in modeling complex physical phenomena across solid‐state physics, hydrodynamics, plasma physics, nonlinear optics, and biological systems. This study focuses on the Shynaray II‐A equation, a relatively less‐explored parametric nonlinear partial differential equation that describes ...
Aamir Farooq   +4 more
wiley   +1 more source

Computing Bonds Between Formal Contexts

open access: yesMathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT The notion of bond was introduced as a technique to aggregate information from multiple datasets without modifying the information already present in each of the datasets. This notion has been extended to several fuzzy frameworks, including the residuated lattice setting, which we also consider in this paper.
Roberto G. Aragón   +2 more
wiley   +1 more source

Algebraic structuralism [PDF]

open access: yesPhilosophical Studies, 2018
openaire   +1 more source

High Relative Accuracy Computations With Covariance Matrices of Order Statistics

open access: yesMathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In many statistical applications, numerical computations with covariance matrices need to be performed. The error made when performing such numerical computations increases with the condition number of the covariance matrix, which is related to the number of variables and the strength of the correlation between the variables. In a recent work,
Juan Baz   +3 more
wiley   +1 more source

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