What is MoSCoW method?

Linear multistep methods are used for the numerical solution of ordinary differential equations. Conceptually, a numerical method starts from an initial point and then takes a short step forward in...

In mathematical logic, especially set theory and model theory, the back-and-forth method is a method for showing isomorphism between countably infinite structures satisfying specified conditions. In particular it can be...

In the mathematical field of enumerative combinatorics, identities are sometimes established by arguments that rely on singling out one "distinguished element" of a set.

The Unit dummy force method provides a convenient means for computing displacements in structural systems. It is applicable for both linear and non-linear material behaviours as well as for systems...

Quantum characteristics are phase-space trajectories that arise in the phase space formulation of quantum mechanics through the Wigner transform of Heisenberg operators of canonical coordinates and momenta. These trajectories obey...

Cognition enhanced Natural language Information Analysis Method is a conceptual fact-based modelling method, that aims to integrate the different dimensions of knowledge: data, rules, processes and semantics. To represent these...

The fast marching method is a numerical method created by James Sethian for solving boundary value problems of the Eikonal equation: Typically, such a problem describes the evolution of a...

In numerical analysis, the local linearization method is a general strategy for designing numerical integrators for differential equations based on a local linearization of the given equation on consecutive time...

In machine learning the random subspace method, also called attribute bagging or feature bagging, is an ensemble learning method that attempts to reduce the correlation between estimators in an ensemble...

The conjugate residual method is an iterative numeric method used for solving systems of linear equations. It's a Krylov subspace method very similar to the much more popular conjugate gradient...