Voltage Regulation for Photovoltaics-Battery-Fuel Systems Using Adaptive Group Method of Data Handling Neural Networks (GMDH-NN)

Band, Shahab S.; Mohammadzadeh, Ardashir; Csiba, Péter; Mosavi, Amir; Várkonyi-Kóczy, Annamária R.

doi:10.1109/access.2020.3037134

Cited by 17 publications

(2 citation statements)

References 28 publications

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“…PDE solutions may be solved using the same numerical techniques used for ODEs. Many difculties may be solved using the techniques mentioned for handling initial value concerns, for example, see references [6,[10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Solving Multispecies Lotka–Volterra Equations by the Daftardar-Gejji and Jafari Method

Batiha

Ghanim

Ala’yed

et al. 2022

International Journal of Mathematics and Mathematical Sciences

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In this article, we apply the Daftardar-Gejji and Jafari method (DJM) to solve the multispecies Lotka–Volterra equation. A comparison between the DJM, differential transformation method (DTM), the variational iteration method (VIM), and Adomian decomposition method (ADM) shows that the DJM is a reliable and powerful method for solving nonlinear equations. The efficiency and applicability of this method are confirmed by considering some examples. The proposed procedure provides better results in comparison to some existing methods.

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Section: Introductionmentioning

confidence: 99%

Solving Multispecies Lotka–Volterra Equations by the Daftardar-Gejji and Jafari Method

Batiha

Ghanim

Ala’yed

et al. 2022

International Journal of Mathematics and Mathematical Sciences

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“…Shahsavar et al [8] changed the GMDH structure and added initial inputs to the input binary combinations in the next layers to propose a generalized GMDH structure for modeling thermal conductivity. Band et al [9] added a sigmoid transfer function to the basic polynomial function of the GMDH method, introduced a neural network-based GMDH (GMDH-NN), and tested it for voltage regulation. Zounemat-Kermani and Mahdavi-Meymand [10] developed the GMDH-FA by the automatic tuning of the GMDH with the silkworm moth algorithm and employed it for the aeration modeling of spillways.…”

Section: Introductionmentioning

confidence: 99%

ML-based group method of data handling: an improvement on the conventional GMDH

Amiri

Soleimani

2021

Complex Intell. Syst.

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Machine learning (ML) has been recognized as a feasible and reliable technique for the modeling of multi-parametric datasets. In real applications, there are different relationships with various complexities between sets of inputs and their corresponding outputs. As a result, various models have been developed with different levels of complexity in the input–output relationships. The group method of data handling (GMDH) employs a family of inductive algorithms for computer-based mathematical modeling grounded on a combination of quadratic and higher neurons in a certain number of variable layers. In this method, a vector of input features is mapped to the expected response by creating a multistage nonlinear pattern. Usually, each neuron of the GMDH is considered a quadratic partial function. In this paper, the basic structure of the GMDH technique is adapted by changing the partial functions to enhance the complexity modeling ability. To accomplish this, popular ML models that have shown reasonable function approximation performance, such as support vector regression and random forest, are used, and the basic polynomial functions in the GMDH are replaced by these ML models. The regression feasibility and validity of the ML-based GMDH models are confirmed by computer simulation.

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A Comparative Study of MARS, GEP, and GMDH Methods for Modeling Soil Thermal Conductivity

et al. 2023

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Voltage Regulation for Photovoltaics-Battery-Fuel Systems Using Adaptive Group Method of Data Handling Neural Networks (GMDH-NN)

Cited by 17 publications

References 28 publications

Solving Multispecies Lotka–Volterra Equations by the Daftardar-Gejji and Jafari Method

Solving Multispecies Lotka–Volterra Equations by the Daftardar-Gejji and Jafari Method

ML-based group method of data handling: an improvement on the conventional GMDH

A Comparative Study of MARS, GEP, and GMDH Methods for Modeling Soil Thermal Conductivity

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