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  2. Regional Input–Output Modeling System - Wikipedia

    en.wikipedia.org/wiki/Regional_InputOutput...

    The Regional InputOutput Modeling System (RIMS II) is a regional economic model developed and maintained by the US Bureau of Economic Analysis (BEA).. Regional inputoutput multipliers such as the RIMS II multipliers allow estimates of how a one-time or sustained increase in economic activity in a particular region will impact other industries located in the region—i.e., estimating ...

  3. Iterative proportional fitting - Wikipedia

    en.wikipedia.org/wiki/Iterative_proportional_fitting

    The iterative proportional fitting procedure (IPF or IPFP, also known as biproportional fitting or biproportion in statistics or economics (input-output analysis, etc.), RAS algorithm [1] in economics, raking in survey statistics, and matrix scaling in computer science) is the operation of finding the fitted matrix which is the closest to an initial matrix but with the row and column totals of ...

  4. Input–output model - Wikipedia

    en.wikipedia.org/wiki/Inputoutput_model

    In economics, an inputoutput model is a quantitative economic model that represents the interdependencies between different sectors of a national economy or different regional economies. [1] Wassily Leontief (1906–1999) is credited with developing this type of analysis and earned the Nobel Prize in Economics for his development of this model.

  5. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    : output vector;: neural network parameters. In words, it is a neural network that maps an input into an output , with the hidden vector playing the role of "memory", a partial record of all previous input-output pairs. At each step, it transforms input to an output, and modifies its "memory" to help it to better perform future processing.

  6. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    In theory, classic RNNs can keep track of arbitrary long-term dependencies in the input sequences. The problem with classic RNNs is computational (or practical) in nature: when training a classic RNN using back-propagation, the long-term gradients which are back-propagated can "vanish", meaning they can tend to zero due to very small numbers creeping into the computations, causing the model to ...

  7. Open energy system models - Wikipedia

    en.wikipedia.org/wiki/Open_energy_system_models

    Open energy system models are energy system models that are open source. [a] However, some of them may use third party proprietary software as part of their workflows to input, process, or output data. Preferably, these models use open data, which facilitates open science. Energy system models are used to explore future energy systems and are ...

  8. Perspective-n-Point - Wikipedia

    en.wikipedia.org/wiki/Perspective-n-Point

    Perspective-n-Point. Perspective-n-Point[1] is the problem of estimating the pose of a calibrated camera given a set of n 3D points in the world and their corresponding 2D projections in the image. The camera pose consists of 6 degrees-of-freedom (DOF) which are made up of the rotation (roll, pitch, and yaw) and 3D translation of the camera ...

  9. IPO model - Wikipedia

    en.wikipedia.org/wiki/IPO_Model

    The input–process–output model. The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process. Many introductory programming and systems analysis texts introduce this as the ...