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Group method of data handling

Group method of data handling (GMDH) is a family of inductive, self-organizing algorithms for mathematical modelling that automatically determines the structure and parameters of models based on empirical data. GMDH iteratively generates and evaluates candidate models, often using polynomial functions, and selects the best-performing ones based on an…

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A simple description of model development using GMDH

GMDH-type neural networks

Software implementations

  • Weka Weka (machine learning)

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Group method of data handling

Nodes47
Edges46
Triples9
Avg. degree1.96
Density0.042553
Components1

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Group method of data handling

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related to External links · 4
Group method of data handling → Data Handling, GMDH, Library, Method

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gmdh models data model algorithms criterion optimal complexity external used neural noise inductive polynomial method one partial approach coefficients learning

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SubjectPredicateObjectConfidenceSrc
singular value decompositioninstance ofThen polynomial coefficients are determined using one of the available minimizing methods0.80text
Single Exponential Smoothinstance ofLi showed that GMDH-type neural network performed better than the classical forecasting algorithms0.80text
Double Exponential Smoothinstance ofLi showed that GMDH-type neural network performed better than the classical forecasting algorithms0.80text
ARIMAinstance ofLi showed that GMDH-type neural network performed better than the classical forecasting algorithms0.80text
back-propagation neural networkinstance ofLi showed that GMDH-type neural network performed better than the classical forecasting algorithms0.80text
Group method of data handlingrelated to External linksLibrary0.60section
Group method of data handlingrelated to External linksGMDH0.60section
Group method of data handlingrelated to External linksMethod0.60section
Group method of data handlingrelated to External linksData Handling0.60section

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