# DESIGNING A SIMPLE RADIOMETRIC SYSTEM TO PREDICT VOID FRACTION PERCENTAGE INDEPENDENT OF FLOW PATTERN USING RADIAL BASIS FUNCTION

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Radial Basis Functions have received significant attention in the scientific literature over the past several years. Specifically, they have been investigated extensively in the field of neural networks. They have been shown to have very good interpolation qualities and this property has led to...

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Cation exchange capacity (CEC), as an important indicator of soil quality, represents the ability of the soil to hold positively charged ions. In this study, CEC was successfully predicted using different statistical methods, including artificial neural networks (ANNs) involving multi-layer...

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Summary: Implantable cardiac pacemaker is a standard medical device to treat heart rhythm disorders. In this paper, a new adaptive backstepping controller is developed to enhance the performance of dualâ€sensor pacemakers for regulating the heart rate based on radial basis function neural...

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The presented work deals with the creation of a new radial basis function artificial neural network-based model of dynamic thermo-mechanical response and damping behavior of thermoplastic elastomers in the whole temperature interval of their entire lifetime and a wide frequency range of dynamic...

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In this article, an adaptive sliding mode fault-tolerant control scheme is proposed to address the problem of robust and fast attitude tracking for a hypersonic vehicle in the presence of unknown external disturbances, additive fault and partial loss of effectiveness fault. Firstly, the healthy...