Short Tutorial on "GMDH in optimization problems"
Group Method of Data Handling in Optimization Problems : A Short tutorial
Group Method of Data Handling(GMDH) is an algorithm that assists in the development and training of polynomial neural network (PNN)-based predictive models. The advantage of PNN models is that they can self-select the number of inputs, network topology, and also the most suitable training algorithm required to optimally and reliably learn the presented problem.
In optimization problems, the GMDH can be used as the optimization technique. Because the method is quick, non-parametric, and cognitive, the identification of the optimal point i,e, will converge fast, and the result will be more reliable than that of non-linear or simple neural network models.
In this aspect, you may refer to the following research publications :
Moshizi, Zahra Gerkani Nezhad, Ommolbanin Bazrafshan, Hadi Ramezani Etedali, Yahya Esmaeilpour, and Brain Collins. "Application of inclusive multiple model for the prediction of saffron water footprint." Agricultural Water Management 277 (2023): 108125.
Emami, Somayeh, Omid Jahandideh, Hossein Yousefi, Hojjat Emami, and Mohammed Achite. "Application of Meta-Heuristic Algorithms in Reservoir Supply Optimization, Case Study: Mahabad Dam in Iran." Journal of Soft Computing in Civil Engineering 7, no. 2 (2023): 98-114.
Pour, Sahar Hadi, Shamsuddin Shahid, and Saad Sh Sammen. "Runoff modeling using group method of data handling and gene expression programming." In Handbook of Hydroinformatics, pp. 353-377. Elsevier, 2023.
Majumder, Priyanka. "An Integrated Trapezoidal Fuzzy FUCOM with Single-valued Neutrosophic Fuzzy MARCOS and GMDH Method to Determine the Alternatives Weight and its Applications in Efficiency Analysis of Water Treatment Plant." Expert Systems with Applications (2023): 120087.
The following tutorial is created to describe how GMDH can be used in optimization problems with the help of the GMDH Shell software. (Available only to paid members)
or Else You may browse the following :
Read the book: Lecture Notes on MCDM
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