Results 11 to 20 of about 26,029 (108)
Mathematical modeling of the spread of the coronavirus under strict social restrictions
Mathematical Methods in the Applied Sciences, EarlyView., 2021 We formulate a simple susceptible‐infectious‐recovery (SIR) model to describe the spread of the coronavirus under strict social restrictions. The transmission rate in this model is exponentially decreasing with time. We find a formula for basic reproduction function and estimate the maximum number of daily infected individuals.
Mo'tassem Al‐arydah +3 more
wiley +1 more source
Advanced Science, EarlyView.A systematic computational framework is developed for practical identifiability analysis in biological models. The framework establishes a rigorous definition, introduces efficient coordinate‐based identifiability metrics, and proposes novel regularization strategies.
Shun Wang, Wenrui Hao
wiley +1 more source
Mapping uncertainty using differentiable programming
AIChE Journal, EarlyView.Abstract Uncertainty quantification (UQ) and propagation is a ubiquitous challenge in science, permeating our field in a general fashion, and its importance cannot be overstated. Recently, the commoditization of differentiable programming, motivated by the development of machine learning, has allowed easier access to tools for evaluating derivatives of
Victor Alves +3 more
wiley +1 more source
Classical-quantum correspondence for shape-invariant systems
, 2015 A quantization procedure, which has recently been introduced for the analysis of Painlev\'e equations, is applied to a general time-independent potential of a Newton equation.
Grundland, A. M., Riglioni, D.
core +1 more source
Computing Periods of Hypersurfaces
, 2019 We give an algorithm to compute the periods of smooth projective hypersurfaces of any dimension. This is an improvement over existing algorithms which could only compute the periods of plane curves.
Sertöz, Emre Can
core +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Dynamic Single‐Input Control of Multistate Multitransition Soft Robotic Actuator
Advanced Intelligent Systems, EarlyView.A concept for reducing the number of control inputs to one in a system with N degrees of freedom, is presented. Incorporating structural instabilities, cleverly, enables choosing any desired trajectory out of (N!)2 with only one input. The concept is demonstrated experimentally, along with analytical insights and numerical simulations.
Geron Yamit +4 more
wiley +1 more source
Twisted symmetries of differential equations [PDF]
, 2009 We review the basic ideas lying at the foundation of the recently developed theory of twisted symmetries of differential equations, and some of its ...
Gaeta, Giuseppe
core +1 more source
Asian Journal of Control, EarlyView.Abstract We study a nonlinear ψ−$$ \psi - $$ Hilfer fractional‐order delay integro‐differential equation ( ψ−$$ \psi - $$ Hilfer FrODIDE) that incorporates N−$$ N- $$ multiple variable time delays. Utilizing the ψ−$$ \psi - $$ Hilfer fractional derivative ( ψ−$$ \psi - $$ Hilfer‐FrD), we investigate the Ulam–Hyers––Rassias (U–H–R), semi‐Ulam–Hyers ...
Cemil Tunç, Osman Tunç
wiley +1 more source
Exponential-Krylov methods for ordinary differential equations
, 2014 This paper develops a new class of exponential-type integrators where all the matrix exponentiations are performed in a single Krylov space of low dimension.
Sandu, Adrian, Tranquilli, Paul
core +1 more source