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This chapter presents a method using artificial simulated wind load to estimate the vibration coefficients.
In this study, a classification-based video super-resolution method using artificial neural network (ANN) is proposed to enhance low-resolution (LR) to high-resolution (HR) frames.
A new method using artificial neural networks for the solution of the unit commitment (UC) and economic dispatch (ED) using Hopfield neural network (HNN) is presented.
Then, a semi-empirical model is developed for the GRMR method using artificial neural network (ANN), and it is validated by a comparative analysis of ANN model results with that by analytical GRMR method.
A method using artificial neural networks (ANNs)—simple mathematical implementations of human brain activity shows promise, but this method also has its own disadvantages, like failing to succeed when limited core plug analysis data are available.
In this paper, we develop a B-spline collocation method using artificial viscosity for solving singularly-perturbed equations given by ϵu″(x)+a(x u′(x)+b(x u(x)="f(x),a(x)≥a∗>0,b(x)≥b∗>0,(0.1)u(0)="α,u(1)="β.
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This method uses artificial way to induce hardening of the paint.
As we mentioned in previous section, navigation methods using artificial magnetic landmarks have been proposed [1].
Autonomous navigation methods using artificial landmarks (e.g. magnetic tapes or makers) have been proposed [1].
This study aims to model the complex modulus of styrene butadiene styrene (SBS) modified bitumen samples that were produced by different methods using artificial neural networks (ANNs).
Votano et al. [13] reported the application of three QSAR methods using artificial neural networks, k-nearest neighbors, and decision forest, to a data set of 3363 diverse compounds.
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