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Several algorithms for modeling systems are proposed in literature.
Algorithms for modeling and calculation of main parameters of nuclear transformations based on directed graphs are suggested, which improves the speed and accuracy of calculations.
Due to the rapid advancement of supercomputing hardware, there is a growing interest in parallel algorithms for modeling the full three-dimensional interaction between the blood flow and the arterial wall.
[Improved PISO algorithms for modeling density varying flow in conjugate fluid-porous domains. Journal of Computational Physics 2016;306:199–215. http://www.sciencedirect.com/science/article/pii/S0021999115007755. http://dx.doi.org/10.1016/j.jcp.2015.11.035;.jcp.2015.11.035
The SAISIR Toolbox for MATLAB, OCTAVE and SCILAB is a freely available collection of functions and algorithms for modeling physicochemical, sensorial and multidimensional data with a large range of bilinear and multilinear models.
Application of soft computing methods (i.e. neural networks and genetic algorithms) for modeling and controlling the dynamic and transient behavior of systems has been increasing during the last decade.
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Young, S. S., Yuan, F. & Zhu, M. Chemical descriptors are more important than learning algorithms for modelling.
There is an increasing interest in reactive distillation, which has led to the development of several good simulation algorithms for modelling these systems.
2004_Matsuka_Corter_Stochastic learning algorithm for modeling human category learning.
John Davis developed an algorithm for modeling the effects of pile-up on ACIS spectral data.
We propose a novel algorithm for modeling interface motions.
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