GMDHGroup Method of Data Handling
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The development of the Group Method of Data Handling (GMDH) algorithm was described by Dag & Yozgaligil (2016) and assumes a time series with t time units and p inputs.
In addition, all the techniques, including the conventional ANN, GRNN, and SVM methods, and the relative novel methods (ELM, ANFIS, and GMDH) proposed by this study remarkably differ in terms of their structures, principles, and parameters.
Differential polynomial neural network (D-PNN) is a new neural network type, which extends the basic complete GMDH PNN structure to form sum series of relative combination derivation terms, which together define and substitute for the selective general partial differential equation (DE) of a multivariable function searched model based on data observations.
Muller, "Present state and new problems of further GMDH development," Systems Analysis Modeling Simulation, vol.
Step 4: using GMDH algorithm in order to predict the influential elements on the waste among the identified elements in step 2.
Even if the IT market does offer a large number of forecasting tools, we consider that one of the most significant one is the GMDH Shell environment, professional neural network software, which solves time series forecasting (Geos Research Group, 2013).
Backpropagation (BP) network, radial basis function neural network (RBFNN), and group method of data handling (GMDH) network are the typical feedforward neural networks.
[2], RK-4, group method of data handling (GMDH), and neuromethod (NM).
Fakhraee compared the accuracy in predicting water demand in Tehran city among three different approaches: regression analysis, time series analysis and GMDH neural network (Fakhraee, 2008).
Group method of data handling (GMDH) (Ivakhnenko 1968).