Jun 24, 2016 · This survey deals with up-to-date results in the field of hybrid algo- rithms development of GMDH-type Neural Networks (GMDH-NN) and other.
This chapter presents a specific encoding scheme to genetically design GMDH-type neural networks based on using a hybrid Genetic Algorithms and SVD to ...
In this paper, for solving the problem of forecasting non-stationary time series, hybrid learning methods for GMDH-neural networks are proposed.
The numerous applications of suggested hybrid DL networks for solution of AI problems like forecasting of share prices and market indicators at various stock.
Missing: Economic | Show results with:Economic
In this paper a GMDH-type neural network and genetic algorithm is developed for stock price prediction of cement sector. For stocks price prediction by GMDH ...
Missing: Solving | Show results with:Solving
In this paper, a GMDH algorithm was developed to predict the viscosity of crude oils. The evident characteristic that was observed in these networks ...
Missing: Solving | Show results with:Solving
The application of GMDH enables not only to train neural weights, but also to construct the network structure as well. Different elementary neurons with two ...
A genetic algorithm and singular value decomposition (SVD) are deployed simultaneously for optimal design of both connectivity configuration and the values ...
Oct 14, 2022 · This paper presents a new approach to solve multi-objective decision-making (DM) problems based on neural networks (NN).
Missing: Economic | Show results with:Economic
Their results showed that the hybrid model can be an effective way to improving predictions achieved when the variables of input layer of ANN is chosen based on ...