Search results
Results From The WOW.Com Content Network
A mesh need not be simplicial because an arbitrary subset of nodes of a cell is not necessarily a cell: e.g., three nodes of a quad does not define a cell. However, two cells intersect at cells: e.g. a quad does not have a node in its interior. The intersection of two cells may be several cells: e.g., two quads may share two edges.
In numerical analysis, adaptive mesh refinement (AMR) is a method of adapting the accuracy of a solution within certain sensitive or turbulent regions of simulation, dynamically and during the time the solution is being calculated.
MATLAB does include standard for and while loops, but (as in other similar applications such as APL and R), using the vectorized notation is encouraged and is often faster to execute. The following code, excerpted from the function magic.m , creates a magic square M for odd values of n (MATLAB function meshgrid is used here to generate square ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
A mathematical markup language is a computer notation for representing mathematical formulae, based on mathematical notation.Specialized markup languages are necessary because computers normally deal with linear text and more limited character sets (although increasing support for Unicode is obsoleting very simple uses).
The test functions used to evaluate the algorithms for MOP were taken from Deb, [4] Binh et al. [5] and Binh. [6] The software developed by Deb can be downloaded, [7] which implements the NSGA-II procedure with GAs, or the program posted on Internet, [8] which implements the NSGA-II procedure with ES.
The mesh is an integral part of the model and must be controlled carefully to give the best results. Generally, the higher the number of elements in a mesh, the more accurate the solution of the discretized problem. However, there is a value at which the results converge, and further mesh refinement does not increase accuracy. [30]
MATHLAB 68 has been used to solve electrical linear circuits using an acausal modeling approach for symbolic circuit analysis. [2] This application was developed as a plug-in for MATHLAB 68 (open-source), building on MATHLAB's linear algebra facilities (Laplace transforms, inverse Laplace transforms and linear algebra manipulation).