In this study, artificial neural networks have been used to model the effects of four important parameters consist of the ratio of the length to diameter, the ratio of the cold outlet diameter to the tube diameter, inlet pressure, and cold mass fraction on the cooling performance of counter flow vortex tube. In this approach, experimental data have been used to train and validate the neural net...

The paper deals with training the neural models of microwave structures. The first, an artificial neural network (ANN) is trained with basic genetic algorithm (GA). Training abilities are discussed. Further, the modification of GA and an approach to learning artificial neural networks (ANN) with backpropagation is described. Neural networks are implemented in MATLAB. Results of training abiliti...

The K-means Fast Learning Artificial Neural Network (KFLANN) is a small neural network bearing two types of parameters, the tolerance, δ and the vigilance, μ. In previous papers, it was shown that the KFLANN was capable of fast and accurate assimilation of data [12]. However, it was still an unsolved issue to determine the suitable values for δ and μ in [12]. This paper continues to follows-up ...

In order to predict PM2.5 concentrations value more accurately, we propose a new prediction technique based on BP artificial neural network model and the multi-population quantum genetic algorithm (this new technique is shorted as MP-QGABP) to improve the PM2.5 concentrations value forecasting system. The MP-QGA-BP model is compared with the traditional BP artificial neural network model for da...

This paper presents a novel approach to solve the hydro plant dispatch problem based on the artificial neural network (ANN) and genetic algorithm (GA). In this work, the difficult water balance constraints are embedded and satisfied throughout the proposed encoding and decoding algorithms. The ANN is used as a pre-dispatch tool to generate raw hydro output for each hour temporarily ignoring tim...

Compressive strength and concrete slump are the most important required parameters for design, depending on many factors such as concrete mix design, concrete material, experimental cases, tester skills, experimental errors etc. Since many of these factors are unknown, and no specific and relatively accurate formulation can be found for strength and slump, therefore, the concrete properties ca...