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This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model.
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While researchers in the field are somewhat critical of outdated methods, in fact, many of them made and still make a profound contribution to the development of methodologies for computational molecular evolution, which explains their frequent usage.
Methodologies for computational analysis can vary widely depending on the question being posed and the experimental data at hand, ranging from highly abstracted models using correlative regression to highly specified models using differential equations, with network component interaction and logic modeling techniques intermediate to these.
We discuss an automated computational methodology for computing two-dimensional spectral submanifolds (SSMs) in autonomous nonlinear mechanical systems of arbitrary degrees of freedom.
A methodology for handling computational difficulties with contour corners is outlined.
In this work, a general methodology for the computational fluid dynamics (CFD) simulation of a bubble separation tank is described.
A methodology for the computational modeling of the fatigue crack growth in pressurized shell structures, based on the finite element method and concepts of Linear Elastic Fracture Mechanics, is presented.
This paper describes a methodology for the computational evaluation of the impact of design decisions on the non-functional requirements of the various stakeholders involved in the development of a system.
The example of ferrous alloys provides a template for a general methodology of computational design for all materials.
The example of high-performance alloys provides the template for a general methodology of computational design for all materials.
The model reduction methodology of computational singular perturbation (CSP) is enhanced for chemical kinetics problems.
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