Modelling and Pareto optimization of heat transfer and flow coefficients in microchannels using GMDH type neural networks and genetic algorithms

Prediction of friction factor of pure water flowing inside vertical smooth and microfin tubes by using artificial neural networks

“…Generated network structures found to have excellent performance compared to classical empirical equations. Amanifard et al [4] used neural networks and genetic algorithm to predict the pressure drop and Nusselt number in microchannels and used these models to determine the optimal design of the channels. Authors successfully applied these methods to the problem and reported important design relationships between different geometric parameters.…”

Modeling and Multi-Objective Optimization of Forward-Curved Blade Centrifugal Fans Using CFD and Neural Networks

“…General connection between inputs and output variables can be expressed by a complicated discrete form of the Volterra functional series in the form of ... (10) where is known as the Kolmogorov-Gabor polynomial [8]. This full form of mathematical description can be represented by a system of partial quadratic polynomials consisting of only two variables (neurons) in the form of There are two main concepts involved within GMDH-type neural networks design, namely, the parametric and the structural identification problems.…”

“…Moreover, there have been many efforts in recent years to deploy GAs to design artificial neural networks since such evolutionary algorithms are particularly useful for dealing with complex problems having large search spaces with many local optima [9]. In this way, GAs has been used in a feed forward GMDH-type neural network for each neuron searching its optimal set of connection with the preceding layer [10]. In the former reference, authors have proposed a hybrid genetic algorithm for a simplified GMDH-type neural network in which the connection of neurons are restricted to adjacent layers.…”

Pareto based multi-objective optimization of a cyclone vortex finder using CFD, GMDH type neural networks and genetic algorithms

“…In this way, GAs has been used in a feed forward GMDH-type neural network for each neuron searching for its optimal set of connections with the preceding layer (Amanifard et al 2008). In the former reference, the authors have proposed a hybrid genetic algorithm for a simplified GMDH-type neural network in which the connection of neurons are restricted to adjacent layers.…”