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  2. Flow-based generative model - Wikipedia

    en.wikipedia.org/wiki/Flow-based_generative_model

    A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.

  3. Lattice Boltzmann methods - Wikipedia

    en.wikipedia.org/wiki/Lattice_Boltzmann_methods

    Schematic of D2Q9 lattice vectors for 2D Lattice Boltzmann. Unlike CFD methods that solve the conservation equations of macroscopic properties (i.e., mass, momentum, and energy) numerically, LBM models the fluid consisting of fictive particles, and such particles perform consecutive propagation and collision processes over a discrete lattice.

  4. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

  5. Hardy Cross method - Wikipedia

    en.wikipedia.org/wiki/Hardy_Cross_method

    Guess the flows in each pipe, making sure that the total in flow is equal to the total out flow at each junction. (The guess doesn't have to be good, but a good guess will reduce the time it takes to find the solution.) Determine each closed loop in the system. For each loop, determine the clockwise head losses and counter-clockwise head losses.

  6. Projection method (fluid dynamics) - Wikipedia

    en.wikipedia.org/wiki/Projection_method_(fluid...

    The algorithm of the projection method is based on the Helmholtz decomposition (sometimes called Helmholtz-Hodge decomposition) of any vector field into a solenoidal part and an irrotational part. Typically, the algorithm consists of two stages.

  7. SIMPLE algorithm - Wikipedia

    en.wikipedia.org/wiki/SIMPLE_algorithm

    In computational fluid dynamics (CFD), the SIMPLE algorithm is a widely used numerical procedure to solve the Navier–Stokes equations. SIMPLE is an acronym for Semi-Implicit Method for Pressure Linked Equations. The SIMPLE algorithm was developed by Prof. Brian Spalding and his student Suhas Patankar at Imperial College London in the early ...

  8. Iowa State basketball vs. Illinois in March Madness ... - AOL

    www.aol.com/iowa-state-basketball-vs-illinois...

    Iowa State vs. Illinois prediction in March Madness. Understandably, this matchup is expected to be close. As of Saturday night on Draftkings, Iowa State was a 2.5-point favorite (-110). The over ...

  9. K-epsilon turbulence model - Wikipedia

    en.wikipedia.org/wiki/K-epsilon_turbulence_model

    The exact k-ε equations contain many unknown and unmeasurable terms. For a much more practical approach, the standard k-ε turbulence model (Launder and Spalding, 1974 [3]) is used which is based on our best understanding of the relevant processes, thus minimizing unknowns and presenting a set of equations which can be applied to a large number of turbulent applications.